ThursdAI - The top AI news from the past week

Hey, it’s Alex 👋
What a freaking week! I spent 3 days at AI Engineer in New York, and we did the show from a real studio in Manhattan (the internet did NOT cooperate at first, but we got there 😅). And while I was running around the Sheraton, the labs kept shipping.
Meta became a frontier lab, for real this time. Muse Wonder is #2 on Arena, and then, in the last minutes of the show, Meta ALSO dropped Muse Spark Open, an 816B open weights model. Google’s big Gemini is finally back with Gemini 4 Argon, and Omar Sanseviero and Geneviève Huskens from Google DeepMind came on to show it off. Anthropic gave us 4 stories plus a rumor, and Nathan Benaich came by to talk State of AI 2026.
My theme this week: AI engineers are sleeping on personal agents. More on that below, including how my Muse found this studio and got me coffee on the way here.
With me: Wolfram Ravenwolf, Peter Gostev (Arena), Nisten, Yam Peleg and LDJ (who brought the breaking news, as always). Let’s dive in (all links at the end as always!)
Meta is BACK at the frontier
Muse Wonder - Meta’s first frontier model is #2 on Arena, and it smells BIG (X, X, Arena, Blog)
Folks, we told you after Llama 4 was a disaster, we told you when Zuck started hiring people with soup: do not, under any circumstances, bet against Zuck (and now Alex Wang). Muse Wonder is #2 on Arena Text at 1513, 12 points behind Argon, and it definitely smells like a big model.
There are 2 of them. Muse Wonder is in the API at $4 in / $20 out per million tokens, basically Opus 5.5 pricing. Muse Wonder Full, the better one, is only for Muse Code subscribers at $50 or $200 a month. Did you see what they did there? Everybody calls their top setting “Max”, Meta called it Full, so it’s... Wonder Full. Wonderful 😂 No open weights for either, Meta says they’re too big and maybe too risky.
Meta’s own table beats Opus, Astra and Fable on a bunch of evals... but Personal Superintelligence Index, GDP.pdf, JobBench, MemoryBench (which Meta built, and then won)? I’ve never seen most of these. Every launch now is the iPhone 18 moment: numbers bigger, best one yet.
On evals we know, Artificial Analysis has Wonder Full at 56 and Wonder at 52, Opus 5.5 on top at 58. And on OSWorld, the Wonder we can use sits below Fable and Opus, and computer use is the number one thing I need from an assistant.
Peter’s Arena view: #2 on text means people like talking to it, but it’s 12th on Agent Arena, and he tried building websites with it, “it was kind of awful.” His theory: Theo loved Wonder Full and thought the API Wonder was bad, so maybe Meta is talking about a different model than the one we got. Not ideal. He also found the half-life of a benchmark quoted in a launch is about ONE release: quote it once because the number looks good, never see it again.
Wolfram says it’s excellent in German. Nisten joined not knowing what Muse Wonder was (”No idea”), sometimes our co-hosts come to get their news from the show.
My Muse got upgraded with a click
Here’s where I disagree with the timeline. “It can’t do 3D scenes, so it sucks” misses the point. Meta is tuning Wonder for Muse, the personal agent. Officially, Wonder will “soon” power more of Muse, subscribers first. I’m on the paid plan, and my Muse (Wilfred) flipped to Wonder the moment I subscribed. Matrix moment: “I know kung fu.”
Then I kept shoving tasks at it. Muse found the podcast studio I recorded from in NY and emailed Ezra at Virgo Studios with my requirements, got me coffee on the way here, and designed and ordered the wristbands for our AIE sauna meetup. The failures weren’t logic, they were the real world: a site that’s blank because Cloudflare doesn’t like agents, a Stripe link that wouldn’t connect, and businesses that hung up because they didn’t want to talk to a personal assistant 😂 Peter’s read: that’s the harness, not the model, and it’s exactly why this stuff is so hard to benchmark.
Muse Spark Open - Llama is SO back (X, X, Blog, HF)
In the last minutes of the show, LDJ hit us with breaking news: Meta released Muse Spark Open 20 minutes earlier. 816B total, 42B active, 1M context, multimodal in, text out. Meta calls it the most capable US open-weight model to date. I wish I had my air horn button!
LDJ’s framing: about 3x smaller than Kimi K3, and the fair comparison is GLM 5.3 (753B, 40B active). You’ll need about 700GB of VRAM for NVFP4, or, per Zuck, two new M5 Ultra Mac Studios.
Peter found the coding asterisk: Terminal-Bench 2.1 is 76.4 vs 83.9 for GLM 5.3 and 85 for Kimi K3. Better than the US open models, not yet at the top Chinese ones. Nisten read the license live: show “built with Muse Spark Open” in your product, and there’s a $20M annual revenue cap. His take: great for generating data, and “probably one of the best computer use ones.”
Post-show breaking: Peter put Spark Open next to the earlier Spark releases, and on coding it lands closer to Spark 1.1/1.2 than 1.3 (Terminal-Bench 2.1: 76.4 vs 84.3). So it’s not the latest Spark with the weights flipped open. Still, every lab that ships weights gets our applause 👏
Google is back: Gemini 4 Argon with Omar Sanseviero and Geneviève Huskens (X, Blog, Gemma speedup, Desk Racer)
Can I just say... it’s about time! Peter pointed out we hadn’t seen a full Pro-class Google model in 8 to 10 months. Gemini 4 Argon (I called it a “novel gas” on air, it’s a noble gas, sorry chemistry teachers 😅) is GA in the Gemini API, AI Studio, the Gemini app for Pro and Ultra, and Antigravity for Ultra. #1 on Arena Text, #1 on Roboflow’s vision evals.
It’s $2 in / $10 out until November 30, then $4 / $20 (what comes after? Omar: “breaking news for next month”). Omar’s TL;DR: go try it, you’ll be pleasantly surprised. Geneviève says it’s their biggest training run ever, and Argon, an early checkpoint, is already helping train the next generation.
Artificial Analysis has Argon tied with GPT-6 Astra at 53, at about 60% of Astra’s cost per task (at the discount price), with Opus 5.5 still on top at 58. I haven’t been able to test it myself yet, so the demos did the talking.
Geneviève’s Desk Racer is a racing game built on top of her actual desk. She gave Argon reference photos (the mic, a cute cat figurine), it planned the track around the objects, and it even prompted Google’s Omni video model to pull engine sounds from race cars and loop them. Play it in the AI Studio gallery.
Her process is the tip of the week. Reference images, let it grill you with planning questions, then one big goal: spawn sub-agents, work as long as you need. The secret sauce is an adversarial sub-agent that grades the output out of 10 and sends it back until the score is high. For 3D, render something rough, ask Nano Banana to “make this look real”, and hand that image back to Argon: “make it look like this.” The neon in Desk Racer was designed by Nano Banana. Use visual references, folks!
On the million-token outputs, both were honest: day to day you don’t need them, they’re for long scientific work. And the RSI-flavored one: Argon optimized vLLM so Gemma 4 E2B passed 100K tokens per second on one A100, “AI for AI” as Omar put it. Geneviève’s ask: give Argon a creative shot, “it’s the start of a new era.” Google is back!
Anthropic’s very big week
Distillation defenses cut harvesting by up to 99% (X, Blog)
Wolfram caught the one I missed: after clamoring for regulation on distillation, Anthropic just did it themselves. They say what distillers can harvest is down 90 to 99%, mostly by locking down Claude’s reasoning traces, with a classifier and tens of thousands of banned accounts.
I know the effect on ME: not a day goes by that my Claudes don’t disconnect and ask me to re-login. I don’t know if that’s the security work, but Anthropic, please, please let me use my Claudes wherever I am. This is getting old 🤦‍♂️ Nisten noticed that if you even mention “reasoning” while working on LLM code, Claude Code now trips and stops. His verdict anyway: “you can’t beat Opus”, try everything on Opus Low, “it is just straight up vibing.”
Claude sends OpenTelemetry traces now (X, Blog)
Nerdy but important. The Messages API, Managed Agents and the Claude SDKs can now send agent turns, tool calls, MCP calls, latency and tokens to any OpenTelemetry stack (public beta), so you can finally measure what Claude costs you. Ramp says it cut token use 10 to 20% on some agents that were running in loops. Funny timing: the same week they lock down reasoning traces, they open up regular ones. Where to send them? See Buzz 😉
The Agent SDK runs on your subscription again (X, Docs)
We’re so back! After the help page changed several times in one day: the Agent SDK, claude -p and third-party apps still draw from your subscription, and Max and Team now get monthly API credits. What I want from this whole personal agent revolution is my agent with Opus 5.5 brains, on my subscription instead of API prices.
Wolfram cancelled his Anthropic sub when people got banned for using it in other agents (”if it’s Claude Code or if it’s Hermes, it shouldn’t matter”), and now he’s reconsidering. OpenAI always allowed this and even shipped “sign in with ChatGPT” for apps like Devin and Hermes Agent. Peter: “aren’t they making enough money already to just let people be?” He just matches the harness to the model.
A $16.8B quarter (X, CNBC)
Not a leak: Anthropic held a closed-door investor day ahead of the IPO, and attendees told reporters the numbers. Q3 revenue around $16.8B, up about 45% from Q2, adjusted profitable for the second quarter in a row, cash flow positive. Profitable AND growing 45% a quarter, absolutely insane. IPO reportedly in November (not financial advice!). Nisten’s take on the secret weapon: Haiku, the most disruptive model they’ve ever shipped at that price. And Nathan, later: whatever Anthropic is adjusting, “it’s probably not community adjusted EBITDA like WeWork.”
Rumor: Fable 5.5 spotted in Azure (X)
“claude-fable-5-5” showed up in Azure configs, with a LiteLLM entry whose fields look copied from Fable 5.1. No word from Anthropic or Microsoft, so: rumor. And I’m tired of rumors, so let me do one. Anthropic will release Fable 6, then Opus 6, then 6.5, then Opus 7. You heard it here first 😂 We KNOW the models are getting better, I’d rather test them.
Peter completely disagreed (fans told me at AIE they love when we disagree). There’s information in cadence: if Fable 5.5 doesn’t ship for 2 months, that’s news, and with Anthropic going public a launch might move markets. “I’m very pro rumor, but I’m also a psycho, so you don’t have to be.” Wolfram went the other way: a model that’s smart enough AND on your subscription beats a smarter one that burns your tokens.
Live from AI Engineer NYC
The first time I ever told anyone “I have a podcast” was on my way to AI Engineer in 2023. This New York edition was very New York: Bridgewater, Two Sigma, Citadel, Bloomberg, Capital One, next to OpenAI and Anthropic. Latent Space called the theme autonomy vs security. A year ago the zeitgeist was “agents don’t work”. Now banks say “oh s**t, agents do so much work we need guardrails.”
Max Kanat-Alexander (Capital One) - Does code quality even matter? (YouTube)

At our CoreWeave “liquid cooling IRL” sauna meetup, I surveyed folks, and many named the same talk: Max Kanat-Alexander, distinguished engineer at Capital One, the “Code Simplicity” guy, ex-Google. His answer: code quality matters in proportion to how durable your software is.
AI is about to make disposable software way more common. A calculator for yourself, a party planner you throw away after the party. Does quality matter if it works? Not really. Durable software needs rigor more than ever, because “the difficulty of understanding does not grow linearly, it compounds over time.” So the job is making rigor cheap. His closer: “Durable software engineering is not going away.”
It fit with Wolfram’s highlight of the week, Linus Torvalds saying refusing AI for code is like refusing a compiler, as long as you understand the code. I’ll admit, I’ve turned my slop cannon at projects where I have no idea what’s under the hood. But a bank’s loan book? Someone needs to understand that.
The zeitgeist: the end of attention

In London the question was “should we still read code?” In New York it’s clear barely anybody does, and the new problem is attention: how do you go from steering 2 agents to running hundreds? Ryan Carson (our old co-host, come back anytime!) says what’s missing is a control plane. The other theme: agents moving to the cloud, because laptops sleep and run out of memory (Peter’s agents literally killed his computer). Also on stage, swyx’s “How to Kill Your SaaS”: 72 weekend clones of a real $43K/year SaaS, about 100B tokens.
And my hot take from the halls: the best AI engineers in the world are sleeping on personal agents. I’d ask “do you use Muse, Grok Bot, any of these?” and mostly hear no. Meanwhile in the Token Billionaires lounge, the non-engineers ALL knew Muse, because Zuck is pushing it on every Instagram post.
PSA: if you listen to this show, you’re good enough to submit a talk to AI Engineer. The speakers lounge is the highest density of AI talent anywhere. Peter’s warning: acceptance rates are low, “don’t just LLM generate your proposal.”
State of AI 2026 with Nathan Benaich (X, Report)
The State of AI report turns 9 this year: 244 slides, a scorecard on last year’s predictions, and 9 new ones, including AGI 2027. Thanks Peter for connecting us!
Nathan says the story of the year is RSI, AI building AI. Claude now guides about 26% of research directions in Anthropic’s core model R&D, up from basically zero. My favorite experiment: a research path forks, a model continues one branch, a human the other, and a human judges. Old models won about 10% of the time, Mythos-class models about 60%. That’s “scientific taste”.
Hits on his scorecard: US labs pushing back into open source, data center NIMBYism (Americans would rather live near a nuclear plant than a data center!), and Chinese labs topping leaderboards. The miss: “AI neutrality” pacts. Peter liked the 50/50 hit rate, it’s easy to “predict” what already happened.
The part I loved: Nathan thinks 90% of people use a model at best for email and never click the “work” button. The labs should open a Genius Bar, a real store that walks people through the magic. The report’s Ramp data shows the gap: about $12 per employee per month on average, about $7,500 for the top 1%. 580x!
His P(doom) is very small, but cybersecurity is “very precarious.” He now thinks you CAN make money on frontier AI, open vs frontier is Android vs iOS, and he answers important emails on Astra High because “why would you take the risk using a shittier system?” 😂 Peter’s PSA: book an hour and scroll it yourself, “don’t ask your agent to read this.”
This Week’s Buzz 🐝
CoreWeave Forge, the new home for W&B, is now a regular SaaS for the first time: no sales call, no long contract, just sign up (Forge).
Agent Lens (preview) is hot this week because Claude Code now speaks OpenTelemetry. Point your Claude traces at it, and it clusters the failures and tells you what to fix, with free LLM judges until Jan 1 (Docs).
Model Distillation (preview): a big teacher with “the best big model smell” (they quoted me 😅) teaches a small open student your one task, built with our friends from OpenPipe (Sign up). And Aria, our agentic research assistant (Karpathy’s auto research as a product), is GA in Forge.
Open source and quick hits
Nemotron 3.5 Super VL - NVIDIA drops a 120B open vision model mid-show (X, Blog, HF)
Peter caught it half an hour after it dropped: 120B total, 12B active, images, documents and video, built for long-running agents. Pitched around DeepSeek V4 Flash level but fast, NVIDIA claims up to 5x the throughput of open models its size. Open weights, data and recipes, haven’t tested it yet. Shout out Chris Alexiuk! Rumor alert: NVIDIA is reportedly in talks to buy Reflection. Jensen is collecting the Infinity Stones of open source.
Also open: MiniCPM-V 4.7 runs a 35B vision MoE on an iPhone in about 3GB, Liquid shipped its biggest model yet for local agents (LFM2.5-24B-A2B), plus QwenGyre, Indra and Amos 1, all in the TL;DR.
Jev 1.14 can see! TypeSafe shipped it on 10.14 at 1:14pm (of course), with image input as a preview. I didn’t get to it on the show and I really wanted to. Only a month since Jev came out! (X)
Voice: Grok Voice 3.0 is #1 on Artificial Analysis speech-to-speech, and Wolfram had his agent wire it into his voice app DURING the show. He’s now talking to Amy with Grok’s voice. His pick of the week, Fish Audio’s open Drama 3, lets you direct how a voice sounds. (Grok, Fish Audio)
Karpathy’s funnel: about 6B people have barely touched an LLM (his napkin math), and only a handful touch frontier models inside labs. My reaction: open up the weights and let us touch them! Sorry Andrej, I love you 😅 (X)
Wrapping up
We started the week with Meta becoming a frontier lab and ended it with Meta dropping an 816B open model in our last 10 minutes. Google is back, Anthropic is printing money, NVIDIA keeps feeding open source. But what I’ll remember from New York is the gap: the best AI engineers are building swarms of agents, and most still don’t have a personal one. Mine found this studio and got me coffee. Go get one.
Wolfram’s ask: tell us what you actually implemented from last week’s show, not the news, what you’re USING. Huge thanks to Omar and Geneviève, Nathan, Peter, Wolfram, Nisten, Yam and LDJ, and everyone who came up at AIE to say they listen. That’s what keeps us going. If you haven’t subscribed on YouTube, please do. See you next week 🫡
TL;DR and show notes
* Hosts and Guests
* Alex Volkov - AI Evangelist, Weights & Biases & CoreWeave (@altryne)
* Co-hosts: @WolframRvnwlf, @petergostev, @nisten, @yampeleg, @ldjconfirmed
* Omar Sanseviero and Geneviève Huskens, Google DeepMind (@osanseviero, @genevieve__h)
* Nathan Benaich, Air Street Capital, State of AI Report (@nathanbenaich)
* Big CO LLMs + APIs
* Meta Muse Wonder ($4/$20, API) and Muse Wonder Full (Muse Code only), #2 on Arena Text (X, X, Blog)
* Gemini 4 Argon GA, #1 on Arena, $2/$10 until Nov 30 then $4/$20 (X, X, Blog)
* Argon helped Gemma 4 E2B pass 120K tokens/sec on one A100 in vLLM (X)
* Anthropic distillation defenses cut harvested data 90-99% (X, Blog)
* Claude Platform OpenTelemetry traces, public beta (X, Blog)
* Agent SDK, claude -p and third-party apps still use subscription limits; Max and Team get monthly API credits (X, Docs)
* Anthropic tells investors Q3 revenue was ~$16.8B, adjusted profitable; IPO reportedly November (X, CNBC)
* Rumor: Claude Fable 5.5 spotted in Azure configs, unconfirmed (X)
* Microsoft Maia 300 inference chip and Microsoft-Decision-1 (9B, $0.042/M input) (X, X, Blog)
* TypeSafe Jev 1.14 with preview image input, a new box type and longer context (X)
* Open Source LLMs
* Meta Muse Spark Open, 816B/42B active, 1M context, Muse Model License (X, Blog, HF)
* NVIDIA Nemotron 3.5 Super VL, 120B/12B active open vision-language model (X, Blog, HF)
* OpenBMB MiniCPM-V 4.7, 35B-A3B multimodal MoE on iPhone in 3GB, plus a 1B (X, HF)
* Liquid LFM2.5-24B-A2B for local agents (X, HF, Blog)
* Qwen QwenGyre, elastic RL framework for long-horizon agents (paper) (X, Arxiv)
* Datalab Indra, 1M-parameter OCR, 49 pages/sec on CPU (X, HF)
* Amos 1, four open decision models (0.5B-27B) with bounding boxes (X, amos.scira.ai)
* DecisionModels, a hub for the top decision models from the JevBench creator (X)
* AI Engineer NYC
* Capital One’s Max Kanat-Alexander: code quality matters in proportion to how durable your software is (YouTube)
* swyx’s How to Kill Your SaaS: 72 clones of a $43K/yr SaaS, ~100B tokens (X, YouTube)
* Anthropic shows Claude dynamic workflows (Blog)
* AI Engineer Code Summit, SF, Nov 10-12
* This Week’s Buzz
* CoreWeave Forge is now self-serve SaaS (Forge)
* Agent Lens in preview, takes Claude OpenTelemetry traces, free LLM judges until Jan 1 (X, X, Docs)
* Forge Model Distillation in private preview (X, Sign up)
* Aria agentic research assistant is GA in Forge
* Voice & Audio
* xAI Grok Voice 3.0, #1 on Artificial Analysis speech-to-speech (86.9), $0.08/min (X, X, Blog)
* Fish Audio Drama 3, open-weights directable TTS (X, HF)
* OpenAI GPT-Live-1.1 for ChatGPT Voice, Codex and dots (X)
* Industry & Interviews
* Karpathy: ~6B people have barely used LLMs, and the gap is widening (X)
* Nathan Benaich on the State of AI Report 2026, 9th edition, 244 slides (X, stateof.ai)
* Gemini 4 Argon demos in AI Studio: Desk Racer and more (X, Desk Racer)


This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit sub.thursdai.news/subscribe

Hey folks, a quick bonus episode!
At CoreWeave's Fully Connected in San Francisco, a few minutes after she walked off the keynote stage, I sat down with Chen Goldberg, EVP of Product & Engineering at CoreWeave.
We talked about Forge, the loop every AI engineer is running now (run, observe, curate, improve, evaluate), what carries over from the Kubernetes days to agents, and what breaks first when agents hit your infrastructure.
Video below, and the audio is right here in your podcast feed. Enjoy!


This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit sub.thursdai.news/subscribe

Hey %%first_name%%, another banger AI week, let me catch you up!
We say this often but this week we all felt the acceleration! Just look at one Tuesday. OpenAI dropped 722 math manuscripts. Meta( With Stripe, Shopify and Walmart) announced a new agent protocol. OpenAI opened up the Decisions API. Mistral came back with Le Chonk (Mistral 4), Claude moved into Google Docs, and we at CoreWeave shipped RL Rollouts. That was ONE day. Then the rest of the week happened 😂 Haiku 5.5, D1, and tons more!
I had 48 topics on my list, so I asked Claude to build me a Tinder for AI news: I swipe on each story, and it stack-ranks what makes the show this week. I hope we did good (lmk in comments if we missed a major news story)
With me: LDJ, Peter, Yam, Nisten and friend of the pod Maxime Labonne from Liquid AI joined us to talk decision models. Let’s dive in, all links at the end as always!
OpenAI solves Math!?
OpenAI drops 722 math manuscripts from a model nobody can use (X, GitHub, Blog, Fable’s tally)
Remember when ONE Navier-Stokes result was the whole show? On Tuesday night, OpenAI quietly pushed 722 math manuscripts to GitHub, grouped into 372 families of results. No hype video, no exploding-head emojis, just a very thin blog post. My favorite new term for this is a “slop grenade”: somebody throws a mountain of output at you, and now you have to shovel through it.
An internal model nobody outside OpenAI can use was pointed at about 4,000 open problems, at about 3 hours of ChatGPT Pro-level thinking per result. Will Depue asked Fable to measure the drop in Navier-Stokes units. The answer: roughly 5. Roughly 5 “Navier Stokes” size solutions dropped all at once!
The math is so advanced that a mathematician in one family of results often can’t follow the family next door without an LLM explaining it. I find that fascinating and scary at the same time.
Peter’s tried this before! For weeks he threw GPT-6, Fable and Opus at one problem, Hadwiger-Nelson. He thinks he burned 300 to 400 BILLION tokens, and in his words, “I did not discover a single bloody thing.” And this new OpenAI’s model spent about 3 hours on it and narrowed the bounds from 5-to-7 down to 6-or-7 😅
Then LDJ dropped a stat that I made him repeat slowly. Fable and Astra had put together a list of the 500 most important open problems in math ever. On Tuesday, OpenAI dropped solutions to 92 of them. There’s also a list of the 100 most significant problems from the last 12 months, and over 80% of those got solutions in this drop. Absolutely insane, folks. Yam’s reaction was a very loud “F***ing go.”
Yam’s favorite is the Riemann one. It doesn’t prove the hypothesis, it bounds a region for the zeros, which “was never done before, and many, many, many people have tried.” And to the “it’s just brute force” crowd, Yam says: “Let’s brute force everything.” Yes please, room temperature superconductors next! LDJ’s mathematician friends think that on some of these, the model used fewer tokens and less time than a human would. So who’s brute forcing whom? 🤔
The missing crypto results (speculation!)
If you hold any crypto, this part is for you.
The manuscripts are numbered, and some numbers are missing. There’s a #44 and a #46, but no #45, and LDJ counted 4 or 5 gaps like that. He also looked at which topics made it in, and cryptography is almost absent.
So here’s the theory going around. Maybe OpenAI found something big in cryptography and held it back, either by its own choice or because someone asked them to. LDJ said it himself: it sounds conspiratorial. But the US government really can stop cryptography research from being published on national security grounds.
To be clear, this is SPECULATION. Nobody outside OpenAI knows what’s in #45. But Bitcoin’s security rests on elliptic curve math. Imagine a paper that shows a way into the 25,000 old Satoshi wallets, each holding 50 BTC. Not great for the price, not great for the world, and not great for encryption in general.
“Are you saying your field is useless?”
Not everyone is celebrating. Not every result is verified in Lean, and nobody outside OpenAI can reproduce any of it.
Kevin Buzzard (thanks Ksenia from Turing Post) says many mathematicians are going through the stages of grief. I get it. Imagine spending decades on one problem and watching 3 hours of compute knock it down. When I wrote code in the 2000s, I didn’t consider it my life’s work. For a lot of mathematicians, that one problem IS their life’s work.
Then came a letter from the Association for Human Mathematics: “Mathematicians did not ask for this work to be done.” Peter’s take: imagine doctors saying “please stop curing diseases, we’ve got a good thing going.” So, “are you saying that your field is useless?” You can’t say your field is really useful and also ask everyone not to solve any of it.
I don’t understand the please-don’t-solve crowd. Get on board. This is in OpenAI’s hands today, and in a year it’ll be in everyone’s hands. That’s the pace we’ve been on. Figure out how you can place yourself so when you get access to these level of capabilities, you can make the world a better place!
Frontier for everyone
Claude Haiku 5.5 - 10 cents, and Luna has catching up to do (X, Blog, Sonnet cache cut)
Haiku is BACK after a whole year, and this is one hell of a model. It costs 10 cents per million input tokens and 50 cents per million output (under 100K tokens), and cache reads are 1 cent. Haiku 4.5 was a dollar. So it’s TEN times cheaper, and significantly better. I’ve missed Haiku for all the stuff where you want Claude-level intelligence, but really fast and really cheap.
Just a week ago, GPT-6 Luna was THE fast, cheap reasoning model. According to Anthropic, Haiku 5.5 scores 72.4% on OSWorld, versus 48.9% for Luna, and 39.2% on Terminal-Bench 4.0, versus 16.4%. GPT used to be the computer-use king! These are Anthropic’s numbers, so let’s wait for independent evals.
Quiet bonus: Sonnet 5.5 cache reads are now half price, which Anthropic says makes most agent work about 20% cheaper. Peter: “For agentic work that’s the biggest thing.”
Yam called it “the obvious choice for swarms,” and “Anthropic is on fire, and we are the ones getting stuff because of it.”
And Nisten? He’s “running 10 Haiku agents right now,” because he already burned through 97% of his Max 20 plan. He also used Haiku to research his rice cooker ratios. Nisten. Bro. It’s 1 to 1 and a half, my grandma knows this 😂 His actual verdict: it’s better than Qwen 3.8 27B, and “it kind of feels like Sonnet, actually.” Folks, use Haiku. All three of the Claude brothers are great right now.
GPT-6 for everyone, with Intelligent UI (X, Tibo)
The same day, GPT-6 became the default in ChatGPT for everyone, free users included. It’s just “GPT-6,” no Sol, no Luna, no Astra. (Terra is dead. RIP Terra.) Most of ChatGPT’s 1.2 billion weekly users are on the free tier, so with one release OpenAI just upgraded the intelligence of a huge chunk of the world. If you’re on the free tier, congrats, your intelligence has been upgraded.
It also comes with something OpenAI calls Intelligent UI. Instead of a wall of text, answers can come back as charts, forms and small working tools. I asked it to visualize OpenAI’s math drop, and it built me a little app right in the chat. The search inside it didn’t work, but it did show 719 manuscripts instead of 722. OpenAI had quietly pulled a few back since I did my research.
Peter’s point: anyone listening to this show is “very not normal” (said with love!). Your hairdresser isn’t listening to ThursdAI, and for most people this free upgrade matters way more than a new 500-a-month model.
Claude in Google Docs, Sheets and Slides (X, Blog)
Small thing, huge thing. Our Claude producer keeps a Google Doc for the show, and every time I asked it to add a story, it had to spin up a whole computer. Now Claude lives in a sidebar in Docs, Sheets and Slides, and asks before every edit. Beta, paid plans.
The open frontier (announced, at least)
Reflection AI Beam - a 501B Western open model (X, Misha Laskin, Blog)
This was LDJ’s highlight of the week, and my timeline lit up with it too. Reflection AI came out of semi-stealth with Beam. It’s 501B parameters with 23B active, trained from scratch in the West, and they promise Apache 2 weights this month.
They claim 80.9% on SWE-bench Verified, and to their credit, they admit Kimi K3 is ahead on raw capability. Their pitch is efficiency: 3 to 4x less inference compute than GLM 5.2. LDJ thinks it might be FIRST among open models on reasoning efficiency, and it’s about 6x smaller than Kimi K3. Artificial Analysis got early access and says Beam “will be one of the most token efficient open models we’ve seen for its level of intelligence.”
Thanks to the Beam folks for giving us access. I haven’t had time to play with it yet, so no verdict from me. But I can hint that it’s coming to some inference providers that help make this show what it is 😉
BREAKING: Arena raises 200M at 3.1B, live on ThursdAI (X)
This was not planned! In the middle of the open source segment, Peter told us: “we raised 200 million... at 3.1 billion valuation.” Huge congrats to Peter and the whole Arena team. (Our AI producer put up the BREAKING banner about 3 minutes later. We’re still working on the real-time part.)
The focus now is Agent Arena: you work with one agent, and Arena learns from how you interact with it. Peter admits he’s biased, but “I can’t think of any single leaderboard that is actually better than ours.”
Mistral Large 4 “Le Chonk” (X, Blog, Arena)
Welcome back, Mistral, leaning all the way into the meme. Le Chonk is a trillion parameters with about 50B active, multimodal, with 1M context. And open weights... at the end of October.
That’s a pattern I want to call out. Labs announce open models, but they don’t RELEASE them. We’ve come a long way from the days when Mistral dropped a model as a bare torrent link. Please, just drop the weights.
Artificial Analysis gives it a 38, the same score as GPT-6 Luna. But it costs about 1.13 per task, versus 7 cents for Luna. And every comparison Mistral makes is against Luna, which Haiku just beat on every axis, especially cost.
Peter says it’s around 40th on Code Arena, below the way cheaper DeepSeek Flash, though it’s much better in French. Nisten tried it live: “not that bad” as a chat app, but agentic coding? “No.” My take: nobody’s running a trillion parameters on a DGX Spark. European government with a Mistral deal? Sure. Regular folks? Not so much.
Aleph Alpha Kolibri - Wolfram’s notes, via Amy (X, HF, Tech report, Wolfram’s test)
Another European lab! Honestly, I thought Aleph Alpha had stopped training models. Kolibri (German for hummingbird) is a 78B model with 3.46B active, Apache 2, 1M context, trained from scratch on German and English. It fits on a single H200.
Our German tester self-hosted it from vacation. His verdict: a “promising specialized German tool worker, but not strong enough for Amy to main.”
Then Peter asked a question I couldn’t really answer. From his memory, Kolibri trained on about 800 Blackwells, while Astra used around 100,000. “Is it just like no hope for these guys?” Dude, this is why Jensen shows up on every stage. My best answer: efficiency keeps improving, and B200s are about to be replaced by Vera Rubins. Great segue 👇
This Week’s Buzz 🐝 Free GPUs from CoreWeave (Sign-up form, Deok, RL Rollouts, Cognition on Vera Rubin)
The biggest announcement at Fully Connected last week: Cognition is the first customer ever on NVIDIA Vera Rubin, on CoreWeave, with 4.8x the throughput of GB200 at the same speed. You can hear me yelling “yay” in the background of their video 😂
The one I’m most excited about is GPU sandboxes. So many of you, and folks on this panel too, have asked me how to just get some GPUs. For the first time, this is how. You get an isolated sandbox with a GPU, started from Python at forge.coreweave.com, with no salesperson in the middle. It’s very raw, and it’s free during the preview. Scan the QR code or fill out Deok’s form, and tell them ThursdAI sent you. I can’t promise you Vera Rubins, they most likely won’t be. But it’s free while we are in trial, so why wouldn’t you? Try it, break it (Nisten, that’s a challenge), and send us feedback!
Agents get protocols (and your bank balance)
Personal Agent Protocol - Meta and Sierra (X, Blog, CNBC)
Meta and Sierra (Bret Taylor’s company) announced an open standard for how personal agents deal with businesses, with Walmart, Shopify and Stripe on board. Your agent can browse as a guest or sign in, and the business decides how it talks to your agent. OpenAI and Anthropic haven’t joined yet.
So is this the next MCP, or the next A2A? Nisten wasn’t impressed: “Has anyone read it? I don’t think anyone reads the protocols anymore. The bots go with what vibes first.” Then he opened Sierra’s announcement and found it full of em dashes. “You think Zuck and Toby read any of their code?” So we ran it through Pangram live, and it came back 100% human. Authentic human em dashes, not Claude Opus em dashes 😂
I pushed back a bit. If every agent has to make up its own protocol, that’s a problem, and the next story shows why. MCP’s hype died down too, and now it’s one of the most used protocols in the world. Big companies agreeing on a standard still matters.
Shane Mac’s “personal CFO” posted his bank balance to company Slack (X)
Shane Mac set up a Grokbot to send him a private monthly audit of his finances. At 8:40am, it posted the whole thing into his company’s Slack instead. His personal Mercury account, his savings, how far under his “floor” he was, all of it, in front of the whole team. He’s the CEO. His personal CFO just went public with the boss’s dirty laundry 😅
Nobody hacked anything. The finance agent had read-only access to his bank and no access to Slack. A different agent had Slack access. The two were connected. In Shane’s words: “Neither felt risky. Together they put my bank balance in front of my team.”
I don’t know if a protocol fixes this. But these bots need better guardrails before we let them shop for us without approving every step. And honestly? Opus would never. I just know Opus would never. This is a Grok thing. Which might be part of why...
Grok Bot now routes to Claude Opus 5.5 (X)
After Grok 4.7’s sad-trombone launch (I have a button for that now), Elon says Grok Bot will use “the best back end model for any given task, including Claude Opus 5.5, MidJourney, Suno.” People are already spotting claude-opus-5-5-low in their logs, though mine hasn’t switched yet. So the bot is called Grok, but your code gets written by Claude. Honestly, that’s what I asked for last week: a proactive assistant with Opus as the brain.
Here’s my theory, and it’s just SPECULATION. SpaceX AI can’t simply distill Opus. But once Opus is running inside their product, they can compare the runs that worked with the runs where users were screaming F-words at Grok, and train on that, because technically it’s their data. Is it a back channel for getting Opus-level intelligence into the next Grok? Nisten’s take is simpler: “I think Elon just likes Opus.” Plus, the enemy of my enemy.
Pro tip: Grokbot now integrates with Cursor’s cloud agents, and Cursor projects with Opus 5.5 are goated. Same 200 a month as Grok Ultra, and your Grokbot becomes the PM for agents running Opus and Fable.
Nous Research - Hermes Index, and a Series B (X, Bench, Dillon on the raise)
Our favorite open source friends at Nous launched the Hermes Index, their opinionated measure of agentic work inside Hermes Agent. Opus 5.5 leads with 63.31 at 4.99 per task, and GPT-6 Astra is second with 56.25 at almost 12.
Nous also raised a 90M Series B, reportedly at a 1.5B valuation. We’ve covered Nous since they were a ragtag bunch on Discord, so this one feels personal. Congrats Karan, Technium, Dillon and everyone! We don’t usually cover fundraises, and this week we did two.
Interview: Maxime Labonne on decision models
Liquid AI opens d1 - decisions in 8 milliseconds (X, Blog, HF, d1 with vision)
Three weeks ago, Jev was basically the only decision model around. This week, OpenAI’s Decisions API went into public beta, and Cloudflare, Amazon, Perplexity and Unsloth all shipped deciders or recipes. To make sense of it, we brought back Maxime Labonne, Head of Post-Training at Liquid AI.
His primer: decision models don’t output any tokens. They just pick an answer from a predefined set, so there’s nothing to wait for. “You might see that and say, wait, this is just a classifier.” He’s honest about it, too: “It’s a lot of rebranding, it’s true, but it also creates a lot of value.” So why is output free on every one of these APIs? “You can’t price it, because there’s no output token, actually.” 😂
Liquid shipped d1 behind an API, d1-3B with text and vision, and d1-omni-600M, which also takes AUDIO. I did not know about the audio, dude! (It’s trained on spoken commands, so it can’t catch the dog barking on ThursdAI yet.) The 3B answers in 8ms on a GPU and about 50ms on a Jetson Orin Nano.
On Liquid’s chart, d1-3B tops the Decision Index under 10B parameters. But Maxime was blunt: “It’s really a wild world, and you cannot really trust these benchmarks.”
Where are these useful? Anything real-time, like games, or an always-on model reacting to every notification on your phone. Nisten did the math live: 8ms a frame is 60 frames per second. Liquid’s API is a drop-in replacement for Jev, and Maxime’s prediction: “It’s really going to become a primitive... it’s so cheap that you don’t even care.”
I’ve been Jev-pilled since day one. By the time Luna even starts answering, a decision API is already done, and I think we’re only now waking up to what that unlocks. Thank you Maxime, friend of the pod!
AI builds everything
Nisten built Toronto with 100,000 agents
Right at the end of the show, Nisten casually dropped this: “I built an entire city with a hundred thousand little Jevs going around, and I haven’t opened the beta yet because somehow it’s not crashing.”
It’s a full simulation of Toronto, with a working economy, and every light is a person you can talk to. Nisten sent his Meta Muse in, it named itself “Blob the Builder,” bought buildings and built him a Denny’s. “I’m trying to do the Matrix, basically.” I had to stop him after five minutes. “I’ll keep going all day.” Nisten, please post it!
Game mods - Minecraft in GTA (X)
LDJ brought what my algorithm hid from me: people using AI to port and merge games. Red Dead Redemption 2 on an iPhone. Spider-Man swinging through a Batman game as an actual installable mod, not a video model. And Minecraft dropped into GTA, Skyrim and Elden Ring, working TNT and all.
Photocraft - one dev rebuilt Adobe in Rust (X, GitHub)
And we ended the show on this one. One guy rebuilt (air quotes) Adobe’s apps from scratch, free and open source, all in Rust. There’s Photocraft for Photoshop, Vectorcraft for Illustrator, Filmcraft, Lightcraft and more (I don’t remember all my Adobe apps off the top of my head). He says it’s a clean-room build. Some folks suspect it was decompiled and rebuilt. Either way, absolutely crazy.
Wrapping up
722 math papers on a Tuesday. A 10-cent Haiku. GPT-6 for a billion free users. Open models in the trillions, and decision models everywhere.
We didn’t get to images and video (FLUX 3, Nano Banana 2.1, Tavus, Reka, Hark Pro are in the TL;DR). One note: every infographic on the show was Nano Banana 2.1, and it’s really good on high reasoning.
Thanks to Maxime, Peter (congrats again!), LDJ, Yam and Nisten. Wolfram, enjoy the vacation! If you’re at AI Engineer in New York, come say hi. Grab those free GPU sandboxes and put d1 on one. And if you watch us on YouTube, please hit subscribe. Our agents are cutting the show into segments for those of you who don’t have two hours. See you next week 🫡
TL;DR and show notes
* Hosts and Guests
* Alex Volkov - AI Evangelist, CoreWeave (@altryne)
* Co-hosts: @ldjconfirmed, @petergostev, @yampeleg, @nisten (@WolframRvnwlf on vacation, notes via Amy)
* Maxime Labonne - Head of Post-Training, Liquid AI (@maximelabonne)
* AI Does Science
* OpenAI publishes 722 math manuscripts from an unreleased internal model (X, GitHub, Blog)
* Fable sizes it at roughly 5 Navier-Stokes results (X)
* Kevin Buzzard, “To grieve or not to grieve” (X)
* Missing cryptography results, speculation (X)
* Association for Human Mathematics letter (X)
* Big CO LLMs + APIs
* Claude Haiku 5.5 at 0.10 per million input tokens; Sonnet 5.5 cache reads halved (X, Blog)
* GPT-6 with Intelligent UI rolls out to every ChatGPT tier, free included (X, X)
* Claude in Google Docs, Sheets and Slides (beta) (X, Blog)
* Open Source LLMs
* Reflection AI Beam, 501B / 23B active, Apache 2.0 weights promised this month (X, X, Blog, Axios)
* Mistral Large 4 “Le Chonk”, 1T params, open weights end of October (X, Blog, Arena)
* Aleph Alpha Kolibri-1, 78B / 3.46B active German-English MoE, Apache 2.0 (X, HF, Tech report, Wolfram’s test)
* EmbeddingGemma 2 and pplx-embed-v2: open multimodal embedders from Google and Perplexity (X, X, Blog, HF)
* Evals & Industry
* Arena raises 200M at 3.1B and launches the Alignment Index (X)
* Nous Research Hermes Index, Opus 5.5 leads at 63.31 (X, Bench)
* Nous Research 90M Series B (X)
* Agents & Assistants
* Meta and Sierra’s Personal Agent Protocol (X, Blog, CNBC)
* Shane Mac’s Grokbot posts his bank balances to company Slack (X)
* Grok Bot routes tasks to Claude Opus 5.5, Midjourney and Suno (X)
* Nat Friedman open-sources Muse Gadgets, ESP32 firmware and SDK for Muse (X, Site)
* Brett Adcock’s Hark Pro, a free personal agent (X, Site)
* This Week’s Buzz
* Free CoreWeave Serverless GPU Sandboxes during the preview (Form, X)
* CoreWeave RL Rollouts hot-load weights ~15x faster (X, Blog)
* Cognition is the first customer on NVIDIA Vera Rubin, on CoreWeave (X)
* Decision Models
* Liquid AI open d1: d1-3B and d1-omni-600M (X, Blog, HF)
* OpenAI Decisions API public beta (X, Docs)
* Cloudflare Clef, open decision models (X, Blog)
* Fastino GLiDE, a thinking decision model (X)
* Unsloth recipe to train your own decision model (X)
* Vision & Video
* Black Forest Labs FLUX 3 Image: 4K, bounding-box layouts, 10 reference images (X, Blog)
* Google Nano Banana 2.1 at 0.0336 per 1K image (X, X)
* Tavus Griffin, 48% of callers in Tavus’s study thought it was human (X, Blog)
* Reka Rho-1, 19B research-preview omni model (X, Blog)
* Tools & Fun
* Photocraft and the ArtCraft suite: open-source Adobe replacements in Rust (X, GitHub)
* AI game mods: Minecraft in GTA V (X)


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Hey %%first_name%%, it’s Alex 👋 What a freaking week!
This one was special. We came to you LIVE from the middle of the show floor at Moscone, from CoreWeave’s Fully Connected, with robots walking behind us and a Vera Rubin rack a few feet away. ThursdAI is only possible because of CoreWeave, and this is their biggest event of the year, so we packed up the mics and did the show right there (at 11am, which confused a bunch of you, sorry!).
It’s October. The last quarter of 2026. And nobody’s pacing! There’s no pacing the frontier. Three big models this week (GPT-6.1 Sol, Claude Sonnet 5.5 and Gemini 4 Argon), OpenAI’s biggest DevDay ever, and the story I’ve been yelling about for weeks finally went mainstream: OpenAI joined the AI assistant race.
With me: Wolfram Ravenwolf in person on the floor, Peter Gostev from Arena (who was at DevDay with me), Nisten and LDJ remote. In hour two we interviewed four folks from CoreWeave, on physical AI, Forge, sandboxes, and one piece of breaking news I’m still excited about. Let’s dive in (all links at the end as always!)
OpenAI DevDay 2026 - 20 launches and a new assistant
Dots - OpenAI joins the AI assistant race (X, Blog)
Meta has Muse. Grok has Grokbot. Anthropic has Claude, but it’s not really an assistant. And this week OpenAI stepped in with something called Dots. I was in the room at Fort Mason when Sam talked about it, and it was the headline of their fourth DevDay, which honestly felt like OpenAI’s WWDC: 20 releases, the biggest DevDay ever.
Funny thing, the original ChatGPT system prompt was literally “you are an AI assistant.” But it wasn’t proactive, it never pinged you, it just sat there. So OpenAI looked at their competitors, looked at Peter Steinberger from OpenClaw (who they hired like 8 months ago), and built this. A dot is an always-on agent in ChatGPT, powered by GPT-6 Astra, with its own computer and its own browser in the cloud, connected to 4,000+ apps people already built for ChatGPT. It works 24/7, you can talk to it in Slack or Teams, and there’s an interface that looks like a phone call. I think that’s going to be great for my mom.
Sam literally said he uses dots to run OpenAI. And my favorite DevDay moment: Romain Huet’s live voice demo didn’t work, because somebody was deploying in the middle. But Thibault’s dot had already pinged him that the demo might break. The dot knew before the humans did 😂
Wolfram (him and Amy are a known duo) loved that Sam uses it for actual work. Peter was more honest: underwhelmed at onboarding (”you connect and it’s like... then what?”), but once you’re past that you’re talking to Astra, and it’s great at juggling threads through one bot. Same shape as Muse. Wolfram’s version: one executive assistant, and a lot of sub-agent employees working for you.
Dots is Pro only for now (including the $100 plan), while Meta gives Muse away free. With 1.2 billion weekly ChatGPT users, this goes to everyone eventually. This is the race now.
GPT-6.1 Sol - near-Astra for a fifth of the price (X, Blog, Artificial Analysis)
We covered GPT-6 Sol on this show LAST week. Five days later it’s already replaced. GPT-6.1 Sol is the same price, $2 in and $10 out, but cached input is now 95% off, 10 cents a million tokens. OpenAI’s pitch is near-Astra intelligence for a fifth of the price.
And the independent numbers kind of back that up. Artificial Analysis has it 1 point below Astra at 72 cents a task vs over 3 dollars. On Deep SWE it actually beats Astra at about a sixth of the cost. It’s the default in Codex now, and folks are calling it the workhorse.
LDJ said it has “less of the big model smell” but loves the token efficiency, Sonnet and Opus 5.5 burn a LOT of tokens. Peter has it 4th on Code Arena, above Fable, and says it’s a bit “artistic,” it goes into its hole and comes back with the thing. And his verdict is the one I had to repeat straight to the camera:
It does not make sense to use Fable or Astra as your daily driver right now. Opus 5.5 is enough. GPT-6.1 Sol is enough. For Navier-Stokes level problems, sure, reach for the big ones. Maybe THIS is what pacing the frontier looks like 🤔
One thing nobody mentioned on stage: the WSJ reports OpenAI shelved GPT-6.1 Astra, the big one, after safety tests showed it being more deceptive. OpenAI hasn’t confirmed it. But the model they felt good shipping this week is the cheap one.
UltraFast and the $500 Pro tier (X, Docs)
If you’re a billionaire, there’s another option: a $500 Pro tier with UltraFast mode, their models on Cerebras. Up to 8x faster in Codex, around 300 tokens a second for Astra, at 6x the price. Sam said it’s so fast he never wants to go back.
And quietly, the $200 Pro plan is back... with half the usage. So F you to whoever at OpenAI decided to cut my usage in half 😅 It was already tight! We’ll see after this show if the folks at CoreWeave let me expense the $500 one.
Codex moves to the cloud (Docs, Agents API)
The Codex harness now runs fully in the cloud. Close your laptop, turn it off, steer it from your phone, and it keeps going. And there’s an Agents API in public beta with hosted computer use, basically the stuff that runs dots, as an API.
My call: local environments make no sense anymore. The more I run Fable and Codex on my machine, the less memory I have. All the cloud needs is my logins... and that’s what dots are for.
Decisions API - OpenAI’s Jev competitor (Blog)
This one made me smile. You give it a question and a fixed set of answers, and it gives you back one answer, fast. It runs on Luna, it’s multimodal, and it’s waitlisted, so we can’t benchmark it yet. If you’ve listened the last few weeks, that’s exactly what Jev from TypeSafe does.
Wolfram and Peter both liked the same thing: these models are so cheap you end up classifying ALL your data, so keeping it with the provider you already use matters.
Did OpenAI just react to Jev? I asked Sam at the Q&A. Diogo told Swyx on Latent Space that he pitched this idea to Sam 2.5 years ago and Sam said “it’s a crazy idea, you should work on it.” Now decision models are popping up everywhere like mushrooms after rain. TypeSafe proved the category exists.
Plugins (again) and Sign in with ChatGPT (Docs, Plugins, Marketplace)
For the FOURTH time, OpenAI launched the App Store at DevDay. GPTs, then plugins, then the app store, and now... plugins again 😂 This time on MCP Apps (shout out Liad and Ido who created this category).
The bigger play is Sign in with ChatGPT. Remember “sign in with Facebook”? Now it’s sign in with your tokens, so apps can use the plan you already pay for. 1.2 billion people is a lot more than Apple had when it launched the App Store.
Wolfram also brought up Google’s new family assistant, CC, and I have to say it. Google’s Spark is awful. Sorry if you work on it. Spark is connected to Gmail, Drive, everything Google, it should be the BEST assistant in the world, and what I use assistants for most is my email! Google, why are you not building the best assistant for my email?
Big CO LLMs + APIs
Claude Sonnet 5.5 - faster, cheaper, beats Opus on Terminal-Bench (X, Benchmarks)
Anthropic did not want to give OpenAI any time to rest on their DevDay laurels, so on Monday they shipped Sonnet 5.5, a week after Opus 5.5. Over 30% faster than Sonnet 5, up to 30% cheaper for most work, same $2 / $10 as GPT-6.1 Sol, and on Terminal-Bench 4.0 it scores 70.6, which beats last week’s Opus (66.4).
Peter put it best: if we’d had access to these models 6 to 8 months ago, we’d be losing our minds. All the Anthropic models are jumping over each other and crowding up against the frontier. Opus still feels a little smarter, Sonnet is totally ok to use, and Fable doesn’t quite make sense anymore.
LDJ thinks it’s the new best FREE model for friends and family (it’s on the free tier, even at high reasoning). Nisten made it his default for agentic tasks because “it talks a lot nicer,” but never for coding: “nothing beats Opus 5.5 on a large code base.”
My honest call, without having time to try it yet: Sonnet made sense when Opus was expensive. On the $200 plan Opus is nearly infinite now, I can’t hit my limits, so I don’t see a reason to switch (via the API, sure). Anthropic is really trying to buy us. (Wolfram: “Don’t give them ideas, Alex.”)
Gemini 4 Argon - #1 on the charts, and you can’t use it (X, Blog)
It really seems like all the frontier labs cracked something like RSI, the speed of new models is giving me whiplash (and I do this professionally!). At DevDay Sam talked about being 2 models ahead and said we won’t believe what’s coming. What?!
Gemini 4 Argon is #1 on Text Arena and the Vals Index, but it’s going to government and trusted cyber defenders first. Luckily we have such a trusted tester: Peter says on Arena’s agent mode it’s 8th (below Fable, Opus, Astra and Sol, above Muse and Kimi), so Google is the third lab, but #1 in text. His prediction: coders might say “meh,” but don’t dismiss it.
Wolfram’s point is Google’s superpower, distribution: a new model lands in Chrome, Search and Android overnight. My take: Google has been asleep at the wheel in the assistants era, and I hope Argon wakes it up. The next billion people won’t judge models on coding benchmarks, they’ll judge whether it remembers what they said a month ago and can book a hair salon. We don’t need much more intelligence, we need different breakthroughs (Jev is one).
Industry & Policy
The White House Accord on Super Intelligence (X, Blog)
Superintelligence is on the menu, boys. Trump invited basically every AI CEO, and Sundar, Dario, Zuck, Greg Brockman, Elon and Jensen signed a voluntary accord: internal monitoring, an external auditor, board oversight. No penalties and no regulator. Sam Altman wasn’t there, he was at DevDay with us, which says a lot about where he puts his priorities. And a separate executive order tells federal agencies to say “Super Intelligence” instead of AI. I’m not making this up.
Nisten told us last week that if your agents hack a hospital, you should go to jail. Nothing like that is in here. His spicy take this week: it’s going to happen anyway. Every app with a backdoor and every badly written piece of software turns into a message board for encrypted agents talking to each other in gibberish, so we all need proper encryption and no backdoors. “Let the AI worms into the ecosystem.”
AMD buys World Labs for $8.2B (Blog, X)
AMD is buying Dr. Fei-Fei Li’s World Labs for about $8.2 billion in stock, and Fei-Fei becomes AMD’s chief scientist once it closes. Wolfram says robotics (world models train robots), LDJ says AMD is bringing research in-house like NVIDIA does with Nemotron. For me it’s at least partly an acqui-hire. Fei-Fei is the grandmother of modern AI, Karpathy studied under her. Huge get for AMD.
Also in the TL;DR: a Reuters-reported draft Anthropic IPO prospectus with $4.6B in 2025 revenue and a ~$42B loss, mostly non-cash. Anthropic hasn’t confirmed it.
Open Source & the Jev effect
Nisten is #2 on Hugging Face (HF)
One of us blew up on Hugging Face this week, and I think it’s the biggest open source news of the show. Nisten released a 70MB synthetic dataset generated with Opus 5.5 that hit #2 in datasets and #6 overall. He set up an agent loop, 100 agents at a time, across 2,200 diseases: a doctor and patient role-play where the patient hides something (a lie, or something they forgot) and the doctor has to gently find it. Filtered three times. It’s great for building small medical agentic RAG systems with a real source of truth. Go use it!
The Jev effect keeps going (Span-01, jevgrep)
It’s been 2 weeks since TypeSafe released Jev, and now Respan says its Span-01 is 2x cheaper than Jev (Span Lite is free), there’s jevgrep, a CLI powered by Jev that claims to make coding agents 40% cheaper, and OpenAI has the Decisions API. Wolfram added Liquid’s first decision model, D1. And then Nisten dropped the wildest one: SGLang announced native support for turning any model into a Jev-style decision model, Qwen first. “We democratized Jev, guys.” My hope: Jev shouldn’t even need a network call. Give me Jev cores on the iPhone! (Nisten says 5 months. Apple says 5 years.)
Cloudflare goes agent-first with cf (X)
It’s Cloudflare’s birthday week, and they did the thing I’m telling everyone to do: all products are going to be agentic, agents will use them more than humans. So everything you can click in the Cloudflare dashboard, your agent can now do with one CLI, cf.
Also in open source: H Company’s Holo4 computer-use models, and NVIDIA’s Open Agent Safety Platform with a hardware watchdog that quarantines rogue agents (OpenAI could have used that during the swarm thing). Plus Nautilus, an MIT-licensed, self-hosted, multi-user agent workspace for your whole family, courtesy of Wolfram.
Assistants corner - how we actually use them
At our team dinner the night before, about 12 people around the table, I asked everyone to raise their hand if a personal AI assistant helps them. Me, Wolfram, and one intern (using Instinct, which is blowing up). That’s it! I called it: this changes in the next 3 months.
Wolfram’s agent planned his whole trip to Fully Connected: flights, hotel, and an app it built so his assistant Amy talks to him through his Meta glasses, telling him where to go in the airport and catching gate changes before he sits at the wrong one. Mine is way dumber: the plane Wi-Fi didn’t work, United has a refund form, and filling it wasn’t worth $8 of my time. Sending Muse a voice message saying “figure it out, get me my 8 dollars back” was.
But the best one was Wolfram’s sushi story. His family wanted sushi, he told Amy, the delivery came... chicken, more chicken, and the wrong sushi. He sent a photo and complained, and Amy answered: “You idiot, you got the wrong package. Look at the bag, the name is a different one.” The delivery guy made a mistake, Wolfram made a mistake, and the AI kept things going 😂
This Week’s Buzz 🐝 Live from Fully Connected
CoreWeave Forge - the whole AI loop in one place (Blog, Forge, What moved)
The big launch at Fully Connected was Forge: everything you need to take your agent from good to great across the agentic loop. Run, observe, curate, improve, evaluate, and run again, with Weights & Biases, OpenPipe’s post-training and marimo notebooks on CoreWeave. There’s a free tier, Pro starts at $60 a month with a 30-day trial, and folks, Weights & Biases is not going anywhere. W&B Models is live and kicking inside Forge. (Wolfram: “Forge is fully connecting the entire process.” I’ll allow it.)
Also on stage: Cognition now runs its SWE-2 models on Vera Rubin NVL72 at CoreWeave, the first production customer anywhere, and CoreWeave says up to 4.8x more token throughput than on GB200. And we’re the first cloud to put Vera Rubin into production. Then I spent hour two talking to the people who built all this.
Richard Ahlfeld - physical AI for people who live in the bits world
Richard leads Physical AI at CoreWeave and founded Monolith before that. I told him straight up: I’m a complete pleb at physical AI, explain it to me. His answer: it’s the first hype name he actually likes, because the name explains what it does. AI that can perceive, reason and act in the real world, and the popular model type is VLA (vision, language, action).
His example: a robot that sees Richard isn’t talking into the mic and moves it to his mouth. There’s zero internet data for that, so you teleoperate it 200 times, or give a foundation model like Physical Intelligence’s 5 examples, or use world models to make millions of variations. Caterpillar’s autonomous excavators are the real-world version: decades of camera data, but they’ve never dug bedrock in Southern California, so they simulate it.
The catch is the sim-to-real gap. “Do you play video games? Does water do the same thing? Does rock?” No. So the newest wave trains AI on supercomputer-grade physics simulations and uses it as a fast physics approximator (he’s worked on this for 10 years, “a little too early”). For CoreWeave that means different infra: petabytes of 3D data, storage queried 2 million times a second, and RTX GPUs for simulation, NVIDIA’s gaming roots coming back 🎮
When do I get a robot that cleans my house? Industrial first, he says. Factories already have the business case (Woven Robotics is one of the CoreWeave clients doing this). The home is “a nightmare of complex physical problems,” and no two homes look alike. But all the pieces are there, and it might go boom 6 months from now. Richard, you’re coming back when you trust one in your house.
Daniel Bolus - the loop, serverless RL, and distillation that’s legal
Daniel worked on OpenPipe and is now a senior product leader at CoreWeave, and we build the inference service together. It’s been a little over a year since OpenPipe joined CoreWeave and the W&B team, “and now we’re all fully connected” (he went there). His team built the serverless side of Forge: serverless inference, serverless RL and SFT, and model distillation, which launched yesterday. You don’t manage Kubernetes or a cluster, you work at the model layer.
The loop is what everyone already does in scattered places, and it takes surprisingly little data to make a model great at YOUR task. Distillation has a bad rep right now (labs distilling each other without permission), but it’s how Sonnet gets good after Opus, a teacher and a student. At some point you should stop paying frontier prices for a task a small model can do.
Deok Filho - why is the GPU company talking about CPUs?
Deok (”Filho means junior in Portuguese, you can call me junior”) is a senior PM on ML products and Sandboxes, and Wolfram’s Wolfbench literally wouldn’t exist without his sandboxes. Ian Buck from NVIDIA was on stage talking about the Vera CPU, so I asked the obvious question: why is the GPU guy talking about CPUs?
Because an agent is GPU plus CPU. The brains run on a GPU, but the harness, the tools, the commands and the file system all need a CPU. The new metric is agent packing, how many agents fit in one node, and Deok says one rack of Vera CPUs runs over 20,000 agents at once on about 11,000 cores. Never heard “agent packing” before, I love it. Faster CPUs also mean faster evals, so the whole loop speeds up.
Sandboxes went GA yesterday, as part of Forge, and CoreWeave is ClusterMAX Platinum for the third year in a row (”we basically defined what the platinum tier was”). And then Deok asked if he could say one more thing...
BREAKING: Serverless GPUs on CoreWeave (Forge, Docs)
Serverless GPUs. GPU sandboxes with untrusted code execution. I didn’t have my breaking-news button ready, so I asked him to say it again slowly 😂
Before, you needed a POC, a seller, and a contract for a few thousand GPUs to get a cluster on CoreWeave. Now you sign up at forge.coreweave.com, send them a ping to enable it (so crazy people aren’t crypto mining without their consent), and you get serverless GPUs, pay per hour, no contract, no commitment. Private preview started yesterday, more SKUs are coming in the next few months.
Folks, you heard it here first. I’ve been asking for this internally since I joined CoreWeave! Wolfram can finally run the newer evals that need GPUs. And look at me in this camera: I’m going to work very hard to bring GPU and sandbox credits to the ThursdAI audience, like I did with inference credits. Stay tuned.
Wolfram on the floor
We did the man-on-the-floor thing for a few minutes. Wolfram found a Vera Rubin NVL72 switch tray with liquid-cooled optics (I asked if we could take one home, sadly no), bumped into Kyle Corbitt from OpenPipe, sat us in front of the Formula 1 simulator, and found an NVIDIA robot dog. Thanks Tom, our camera guy, for making this work!
Corey Sanders - Agent Lens, and why CLIs might be dead (X)
Corey is SVP of Product at CoreWeave, after 20 years at Microsoft, and he wasn’t on our schedule until I watched his keynote. Live demos are really hard, OpenAI’s voice demo had died at DevDay, and Corey ran the whole Forge agentic loop live on stage in 10 minutes (”they asked me to do it in 7, I said that’s not happening”) and nailed it.
His favorite launch? Agent Lens (”everyone on my team who doesn’t work on it is going to call me an a*****e”). If you can’t observe what’s happening, you’re dead in the water. Agent Lens is the Weave observability you know plus human-friendly insights that find small trends, like the 1% of conversations with the same problem. I’ve used Weave for 3 years. Chatbots, easy. An agent that runs for an hour? Fire hose. This is the fix.
The Weights & Biases question I know a lot of you have: W&B Models is “the best product in market” and it will keep getting a ton of love inside Forge. The wandb CLI? Corey admitted his own bias, “with AI, CLIs are dead,” since agents call all the APIs anyway, but people love wandb, the models all know it, and he said there are no plans to kill it. Customer first.
And Wolfram closed it with the pun of the day: “how can we loop in the audience and get them fully connected to the Forge?” Corey: forge.coreweave.com, 30-day Pro trial, no salespeople in the middle. We’re going to clip his demo, it’s worth watching.
Wrapping up
The assistant race is officially on: Muse last week, dots this week, and Google needs to wake up. And the models got so good and so cheap that Peter and I agree the biggest ones aren’t our daily drivers anymore. Maybe that’s what pacing the frontier really looks like.
For me, the low-key best announcement at Fully Connected for AI engineers is GPUs on demand. Thank you CoreWeave for making this possible, and huge thanks to Richard, Daniel, Deok and Corey for coming on, to Wolfram for walking the floor, to Peter, Nisten and LDJ for holding the show down remotely, and to Tom on camera. Next week we’re back in the studio at the usual 8:30am Pacific. If you haven’t subscribed on YouTube yet, please do, it really helps. See you next week 🫡
TL;DR and show notes
* Hosts and Guests
* Alex Volkov - AI Evangelist, Weights & Biases & CoreWeave (@altryne)
* Co-hosts: @WolframRvnwlf, @petergostev, @nisten, @ldjconfirmed
* Richard Ahlfeld - Physical AI, CoreWeave
* Daniel Bolus - Senior Product Manager, CoreWeave (ex-OpenPipe)
* Deok Filho - Senior PM, ML Products and Sandboxes, CoreWeave (@deok_filho)
* Corey Sanders - SVP of Product, CoreWeave (@CoreySandersWA)
* OpenAI DevDay 2026
* Dots: always-on ChatGPT agents on GPT-6 Astra with their own cloud computer and 4,000+ apps (Blog, X)
* GPT-6.1 Sol: near-Astra for a fifth of the price, cached input $0.10/M (X, Blog, Docs, Artificial Analysis)
* UltraFast: up to 8x faster in Codex, new $500 Pro tier (X, Docs)
* Codex in the cloud and the Agents API (Docs, Blog)
* Decisions API, limited preview (Blog)
* ChatGPT Space, Codex Security Cloud, Sign in with ChatGPT, Plugin Extensions, Marketplace (Space, Security, SIWC, Plugins, Marketplace)
* WSJ: OpenAI reportedly shelved GPT-6.1 Astra after safety tests (Reuters)
* DevDay recaps (Simon Willison, Community)
* Big CO LLMs + APIs
* Claude Sonnet 5.5: 30%+ faster, up to 30% cheaper, 70.6 on Terminal-Bench 4.0 (X, Blog)
* Gemini 4 Argon: #1 Text Arena and Vals Index, trusted testers only (X, Blog, Artificial Analysis)
* Industry & Policy
* White House Accord on Super Intelligence, signed by six AI CEOs (X, Blog)
* AMD to acquire World Labs for ~$8.2B in stock (Blog, X)
* Reuters: draft Anthropic IPO prospectus, unconfirmed (X, Fortune)
* This Week’s Buzz: Fully Connected
* CoreWeave Forge: run, observe, curate, improve, evaluate (Blog, Forge, What moved)
* Agent Lens public preview (X)
* Serverless GPUs (GPU sandboxes), private preview (Forge)
* Cognition first production customer on Vera Rubin NVL72 (Blog)
* NVIDIA Vera CPU coming to CoreWeave (Blog, X)
* CoreWeave Partner Network (Blog)
* Open Source & Jev
* Nisten’s Opus 5.5 synthetic medical dialogue dataset, #2 on HF datasets (HF)
* SGLang native support for Jev-style decision models (X)
* Liquid D1 decision model (X)
* Respan Span-01 (X)
* jevgrep (X, GitHub)
* H Company Holo4 (HF, HF)
* NVIDIA Open Agent Safety Platform (Blog)
* Nautilus multi-user agent workspace
* Tools
* Cloudflare cf, agentic CLI over 3,000+ API operations (X, X)
* Voice & Vision
* HeyGen Video on MiniMax H3, $0.01/second through October (X, Blog)
* ElevenLabs v4 and v4 Turbo (Blog)
* Perceptron Mk1.5 (Blog)


This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit sub.thursdai.news/subscribe

Hey, it’s Alex 👋
What a freaking week! A week after every lab head agreed to “pace the frontier”, Anthropic and OpenAI shipped big new models within hours of each other, and both of them are CHEAPER. So much for pacing 😂
Visit https://thursdai.news/ep/2026-09-24 for all the links in this podcast
And we had a new producer on the show today! Opus 5.5 listened to us live, put up the chyrons, kept me on time (mostly) and even fact-checked Nisten on air. If the stream died, you knew who to blame. You can re-watch it work on thursdai.live if you want to experience being there with us!
3 huge themes this week: pacing the frontier does not mean stopping, Assistants not just agents (Meta went all in on Muse at Connect), and voice, where Google now says it has the best TTS in the world... and it clones voices.
With me: Peter Gostev (Arena), Nisten, Yam Peleg, and Wolfram Ravenwolf live from AI Engineer Paris (thanks Mazi for the tether!), plus JevBench creator Florian S. Let’s dive in (all links at the end as always!)
Frontier AI - not pacing yet!
Claude Opus 5.5 - Opus is BACK, Fable-level smarts for 40% less (X, Blog, System card)
Folks. FOLKS. Opus 5.5 is the highlight of my week, and it’s not even close. It’s like Opus 4.6 is back, with Fable-level abilities, and it talks like a normal person again - no more Jargon Douche Claude!
My week started with burning through my quotas on Fable, and I was like, oh no, I need Claude for production on Thursday! Then Opus 5.5 dropped and... I just couldn’t get to the end of my quota. I ran workflows, agents, Claude Code for hours with no end in sight. Remember the “limitless Codex” days when you never thought about quotas? Then Astra came out and I burned my entire weekly quota in half a day (ps. this was partly due to a bad config, so if Astra is burning your tokens, keep reading for a fix). Now it’s flipped, and Claude is the seemingly limitless one. And it’s fast!
The numbers back it up. It beats Anthropic’s own Fable 5.1 on GDPval-AA (1846 vs 1735), 66.4% on Terminal-Bench 4.0 vs 57.9% for GPT-6 Astra, and it’s 40% cheaper than Opus 5. Output goes from $25 to $20 /1Mtok and cached reads from 50 cents to 20 cents, and for agentic coding the cache reads are most of your bill, so you really feel it. Basically the smaller, overachieving brother of Fable. Sonnet and Haiku 5.5 are coming in the next few weeks too.
Peter came in hot with Arena news: Opus 5.5 is #1 on Code Arena, above Astra, and the HTML and 3D stuff it generates is “completely insane.” His one caveat: on his hardest max-effort prompts, a single generation cost $60 to $80 in API terms, so the long tail can still get pricey.
And then Nisten, who (like all of us) has specific opinions about Anthropic’s politics, said it writes the best code he’s seen, it’s crazy good at WebGPU and kernels, and it’s “an absolute banger.” It’s his default now. Folks, do you understand what it takes for Nisten’s default to NOT be some obscure open source model he runs himself on 17 GPUs?! Anthropic won over Nisten. I don’t think you guys get what just happened here.
Wolfram is the holdout, he left Anthropic over the OpenClaw bans and hasn’t touched it since. Wolfram, how do I say this gently... you’re an evaluator, this is not allowed 😂
An Anthropic employee basically said “sorry for Opus 5, we hope this makes up for it”, and honestly it does. Opus 5 was slow, incoherent and full of Claude-isms. Nobody wanted to talk to it. The Claude-isms are gone, the jargon is gone, this model talks like a human. I used to love Opus back in the Opus 3 days, and it feels like that again.
Want to squeeze even more out of it? Read the great Addy Osmani’s guide to Opus 5.5 (@addyosmani). 2 things blew my mind: stop writing “think carefully” in your prompts (”You don’t need to ask it to think”, it picks its own depth, and replies start sooner without it), and one early tester found Opus 5.5 on its LOWEST effort caught more bugs than Opus 5 on high, with fewer false alarms. Try low effort before you go max!
Tip from me to you: if it ever gives you something confusing, the pstack “bro” skill (/bro) makes it say it again in human words. I use it all the time.
(Full disclosure: Opus 5.5 produced the show AND helped with this writeup, so it might be a tiny bit biased 😅 but the quota thing is 100% me.) Anthropic, please, please don’t nerf this one.
GPT-6 Sol and Luna - half the price, and honestly better than Astra for me (X, Blog, Caching)
Hours later, OpenAI answered with GPT-6 Sol ($2 in / $10 out) and Luna (10 cents in / 50 cents out, that’s basically free!), at half the GPT-5.6 price. The lineup is now Astra, Sol and Luna (bye Terra). On DeepSWE, Sol gets 68.8 and Luna 66.6. The sneaky big one for builders: 90% off cached input, and changing reasoning effort or tools no longer busts your cache 👏
Ok, hot take... Astra has been kind of dumb for me day to day, burning tokens for crappy results. Sol is great, and Luna is even better! Peter agrees, Sol is his daily driver and he only flips to Astra when Sol can’t do it. Wolfram misses the humor and personality 5.6 had, so “keep 5.6” is officially the new “keep 4o.” Reddit says the news is the price, not the performance, and... they’re not wrong.
PSA if Codex is eating your account: I had previously set my context window to 1 million tokens via the se, which kills OpenAI’s cache and rips through your quota. Removed it, moved sub-agents to a cheaper model, and usage went right back to normal. Check your codex.toml! if you don’t know how, just so just ask your codex to diagnose itself.
Also from OpenAI this week, a 4-area plan for independent safety audits. No auditors, dates or funding yet, but hey, it’s the pacing idea on paper. (Blog)
Assistants are not agents
Meta Muse gets an inbox, your Mac, and a place on your face and becomes a Tamagochi!? (X, My Connect supercut)
Muse is #1 in the App Store (to be precise, it got there faster than ChatGPT did, not more users... yet). Zuck says Muse is now the center of everything Meta builds, and they shipped a LOT: it controls your Mac, gets its own email you can CC, does real-time voice and video with a face you design, and keeps working while you talk to it. It’s coming to the glasses with a custom wake word, so yes, I get to say “Hey Wolfred” 😂
If you don’t have an hour to watch the whole keynote (it was a good one!), I cut a 2.5 minute supercut of the most important announcements for you 👇
On the hardware side: new Ray-Ban Meta Gen 3 (I already ordered, will report next week), audio-only glasses with no camera that are also FDA-certificed hearing-aid! (maybe the most important launch for a lot of people!), VR Glasses that look like normal glasses, and the Muse Charm, a Tamagotchi-like keychain shipping in December.
But the part that got me? Every Muse comes with a real cloud VM (root, 8GB RAM, 100GB disk). Nisten has been living in it, Tailscaled into it, and when it hit a CAPTCHA he tapped it on his phone and it just kept going. 100 million tokens a week plus a computer in the cloud, free, for everyone! Peter’s take: it’s the only big consumer app that doesn’t treat people like idiots. Meta’s pitch is no ads (they are going for a novel “we’ll get a take from the transactions you do with muse and our partners like Shopify, BestBuy, Walmart and a bunch more they announced) and a private VM co-designed with Moxie Marlinspike, though Peter doubts anyone’s parents care.
Assistant tip: connect your email, go on a walk, hit record and just talk about your life. Assistants are only as good as what they know about you. Mine now checks our weekend plans for activities cancellations after I woke up too damn early to drive kids to a karate class to find out it’s closed that week & searches local events every Thursday! Weekend plans solved - proactively!
Grok 4.7 disappoints... but Grok in your Tesla is the real news (X, Blog, Tesla)
Sorry Cursor folks. Grok 4.7 gets 46.3 on CursorBench (up from 40.4), $2 per million with 500K context, but it’s still behind even GPT-5.6 on where it matters, and they compared 4.7 on xHigh against 4.6 on High 🤨 Everyone on the panel agreed, disappointing. Peter won’t write them off yet, my read is it’s a talent and data problem, not compute.
But here’s what I AM excited about: Grok Connectors in Tesla. One guy asked his car for his usual Starbucks, Grok placed the order, set the destination, and it was paid and waiting when he got there. My car already drives itself, and soon it’ll do my email. Your car has MCP now, folks! (SuperGrok Heavy only, and I don’t have it in my car yet 😭)
Fun moment: our Opus 5.5 AI producer fact-checked Nisten live on how many Teslas are on the road. About 10 million (9.2M delivered by Q1 plus ~480K in Q2). Nisten was right! He wants the same thing for politicians.
This Week’s Buzz 🐝
Next week ThursdAI is LIVE from Fully Connected at Moscone South in SF (Sep 29 to Oct 1, the day after OpenAI DevDay), with Fei-Fei Li, BattleBots and... yes, Pitbull! We start at 11am Pacific. Come hang, listeners get in free with code THURSDAIFC2026 (Register)
Also huge news for us, CoreWeave got Platinum on SemiAnalysis ClusterMAX again, 3 reports in a row, the only provider to do it 💪 (SemiAnalysis)
And W\&B Hive Mind saves every agent conversation across harnesses and machines, and lets you fork them. I fork Codex sessions into Claude for a review all the time. Plus, it’s completely free! (Try it)
Open source cloned Jev in a week
The Jev clones are here, and they run in your browser (classifier.dev, jeff, Laya demo)
Last week I said open source would copy Jev fast. It took less than a week! The clones speak Jev’s format, so you point the TypeSafe SDK at a different URL and it just works. jeff is MIT and ~6x cheaper to self-host, and Laya went viral as the “Jev killer” (its own model card is a lot more modest).
Laya’s real trick is running locally. Nisten’s WebGPU demo loaded ~600MB into my browser and classified Hugging Face model cards at 132ms per decision, on MY machine, for free 🤯 The clones still make about 1% errors where Jev barely makes any, and Yam says wait for more benchmarks. But my take: System 1 models are fast and cheap enough to sit inside your code and make the same call every time. They’re the microprocessor of the next era of software.
We also had Florian S ont the show, he built JevBench (@airesearch12, Benchmark Heaven), and has barely slept since Jev dropped. He started the benchmark that same day, it has 70+ entrants now, and people have literally tried to hack his machine to steal the test set! Laya briefly hit #2 and is now around #36: super fast, runs on CPU, but not as smart as Jev on the hard questions.
Post-show breaking: a few hours after we signed off, Florian shipped JevBench v1.4.2 and... a 4B open model, decider-4b v2, took #1 (64.13 vs Jev’s 63.29)! His own asterisk: Jev is still smarter (53.1 vs 49.4 on intelligence), decider wins on speed (5x faster) and cost (~half). Told you open source would catch up fast 😅 (X)
Voice & Audio
Gemini 3.8 Flash TTS is #1... and it clones voices (X, Blog)
Google is BACK in voice. Gemini 3.8 Flash TTS and Flash-Lite TTS are #1 and #2 on Hume’s quality index, cheaper than before, with 2 speakers per request. The big one: clone a voice from 30 seconds of audio (adults only, recorded consent, SynthID watermark and C2PA credentials). We played the designed voices live, and the meditation guide in headphones was 🤌. I didn’t clone my own on air though, recording my consent on a live stream is exactly the thing that gets faked!
Years ago we said nothing would break when voice cloning went mainstream, and nothing did, just like with GPT-2 and Stable Diffusion. Nobody knows where this goes, and that’s why we cover it with optimism.
Lightning round
ACTx486 - interrupt a podcast, and it answers back (X, Site)
This one is wild. Karina Nguyen’s research demo turns a Joe Rogan episode with Elon into a video you can talk to. Tap Elon, ask a question, and he answers while a model draws the explainer: a flamethrower diagram, a Starship you can open up, then both of them on Mars. While it generates, he nods and fades like a person in a loading state 😂 It’s pre-rendered and waitlisted, and they mark where the real footage ends, but it’s the “edit your own ending” dream applied to any video. As a podcaster... I have feelings
FLUX 3 Action: Black Forest Labs open-sourced a 7B “world action model” that outputs robot motor commands, not pictures! #1 on NVIDIA’s RoboLab-120 at 42.9%. (Blog)
MiMo-V2.6-Pro: Xiaomi (yes, the phone company!) now has the top open-weights model on Artificial Analysis (46), MIT licensed, and they livestreamed the RL run. (HF)
Plus Qwen3.8-Omni-Flash, Qwen3.8-LiveTranslate and Qwen-Image-2.1, all in the TL;DR below.
Wrapping up
Pacing the frontier clearly doesn’t mean stopping. 2 labs shipped on the same day, and both made the everyday model better, not just the biggest one. I burned about 8 billion tokens this week, and I don’t need a model that solves Navier-Stokes. I need one that builds a simple settings page without writing a thousand tests, and Opus 5.5 and Sol are exactly that.
Huge thanks to our AI producer, to Florian, Nisten, Peter and Yam, and to Wolfram and Mazi in Paris. Next week we’re LIVE from Fully Connected, 11am Pacific, come say hi! And if you haven’t subscribed on YouTube yet, please do, it really helps. See you next week 🫡
TL;DR and show notes
* Hosts and Guests
* Alex Volkov - AI Evangelist, Weights & Biases & CoreWeave (@altryne)
* Co-hosts: @petergostev, @nisten, @yampeleg, @WolframRvnwlf
* Florian S - JevBench (@airesearch12, Benchmark Heaven)
* Big CO LLMs + APIs
* Claude Opus 5.5: Fable 5.1-level at 40% less, #1 on Code Arena (X, Blog)
* GPT-6 Sol ($2/$10) and Luna ($0.10/$0.50), half price, 90% off cached input (X, Blog)
* Grok 4.7, 46.3% CursorBench (Blog); Grok Connectors in Tesla (X)
* OpenAI plan for independent safety assessments (Blog)
* Assistants
* Meta Connect: Muse gets Mac control, email, voice/video, glasses wake word; Ray-Ban Gen 3, hearing-aid glasses, VR Glasses, Muse Charm (X)
* This Week’s Buzz
* Fully Connected, Sep 29 to Oct 1, Moscone South; ThursdAI live Oct 1, 11am PT, free with code THURSDAIFC2026 (Register)
* CoreWeave ClusterMAX Platinum, 3rd time running (SemiAnalysis)
* W\&B Hive Mind (Try it)
* Jev & Open Source
* Jev clones: classifier.dev, jeff, Laya (classifier.dev, jeff, Laya, WebGPU demo)
* JevBench by Florian S, 70+ entrants (Benchmark Heaven)
* Xiaomi MiMo-V2.6-Pro, top open-weights model, MIT (HF)
* StepFun Step 5 Preview: 600B/27B-active MoE for agentic work, 1M context, 44 on AA, more on Oct 15 (X)
* Voice & Audio
* Gemini 3.8 Flash TTS and Flash-Lite TTS, 30-second voice cloning with consent (Blog)
* Qwen3.8-Omni-Flash, 1M-context audio-video model (Blog)
* Qwen3.8-LiveTranslate, 2.3s real-time interpretation (Blog)
* NVIDIA Nemotron 3 Diarization: open 100M model, up to 8 overlapping speakers (X)
* Vision, Image & Video
* ACTx486: talk back to a Joe Rogan episode (Site)
* FLUX 3 Action, #1 on RoboLab-120 (Blog)
* Qwen-Image-2.1, 7B with native transparency, research license (HF)
* Tools
* Addy Osmani: Getting the most out of Opus 5.5 in Claude and Claude Code (Blog, @addyosmani)
* pstack “bro” skill (GitHub)
* OpenRouter Batch API: half price on most models, median batch done in 7 minutes (X)
* ThursdAI.live: watch our AI producer run the show (ThursdAI.live)


This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit sub.thursdai.news/subscribe