Claudiu Micu | Building Wakebound @_MrCode_

GPT-6 Luna and GPT-6.1 Sol by @OpenAI now hold 6 of the 11 spots on the Agent Arena Pareto frontier across their reasoning efforts! - GPT-6 Luna dominates below $0.10/task, claiming 3 of the 4 optimal spots with Max, Medium and Low. - GPT-6.1 Sol sets the frontier between $0.22 and $0.65/task, with the same reasoning levels on it too. This shows why test-time scaling matters. Sometimes the best move is to switch the reasoning effort, not the model, to stay at the optimal cost/performance point. With GPT-6 Astra (Max) also on the Pareto frontier, OpenAI models hold 7 of the 11 frontier spots with multiple reasoning levels. Congrats to the @OpenAI team!

Arena.ai @arena

3 weeks ago

Update to the Agent Arena Pareto frontier: GPT-6 Luna (Max) has landed on the Agent Arena Pareto frontier with +1.59% net improvement at a median cost of just $0.05 per task! Luna costs 29% less than DeepSeek-V4.1-Flash and 76% less than Hy4 preview, while trailing their

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Reuters: OpenAI is rushing a raise at $1.4T+ to land before Anthropic's IPO, expected mid-November. Last priced rounds: Anthropic: $965B (May) OpenAI: $852B Funny race. The one listing first is already the pricier one, and it sets the bar for the other. x.com/Reuters/status…

Reuters @Reuters

18 hours ago

OpenAI is racing to secure investor commitments before rival Anthropic's expected public market debut in mid-November, in an unusually fast fundraising that could value the ChatGPT maker at over $1.4 trillion, according to sources reut.rs/4Bh4Mio

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Anthropic's quarterly revenue this year, per numbers told to investors: Q1: $4.7B Q2: $11.6B Q3: $16.8B 3.6x in two quarters. Asterisk: Anthropic books cloud-partner sales gross, OpenAI reports net. So $67B annualized vs OpenAI's ~$50B isn't apples to apples. Still wild.

@mayankbhaskarr @arena I'd flip the DeepSeek part. It's at ~$52B vs Moonshot's $50B, and reportedly raising near $75B. Open weights didn't cost it much. The real discount is Mistral: $24B on about the same ~$1B revenue. Being #111 on @arena hurts more than open source does.

Three AI labs, each at roughly $1B in annual revenue: Moonshot (Kimi): valued at $50B DeepSeek: ~$52B (revenue estimated) Mistral: $24B Same top line, 2x apart on price. Best @arena rank: Kimi #18, DeepSeek #38, Mistral #111. Investors price the model.

@spacexai @arena Full table, receipts and methodology: airacescoreboard.com/?utm_source=x&… New standings every Monday. Issue #1 of the newsletter is already out (free, 2-min read): airacescoreboard.com/?utm_source=x&… Sponsor slots are self-serve: airacescoreboard.com/sponsor/?utm_s… Wrong number? Reply and I'll fix it publicly.

@spacexai @arena How it's scored: Arena 35 + AA Intelligence Index 15 + revenue 20 + valuation 10 + Polymarket odds 20. No public number means the component is dropped, never guessed. Full formula on the site.

I built a scoreboard for the AI race. One score per lab: model rankings + revenue + valuation + prediction-market odds. Every number has a receipt. Week 1 and we already have a new #1: Anthropic just took the crown from Google DeepMind. 👑🧵

🚀 Introducing DeepInfer, our in-house inference framework, now fully open source! Powering DeepSeek-V4.1-Flash at scale with high throughput and low latency. We’re sharing our production stack to help the community lower compute costs, reduce energy use, and make AI more affordable. 🔗 github.com/deepseek-ai/De… 1/4

@timur_found Yep. Power gets you into the race, it doesn't pay the bills. Curious which gap closes first: xAI's revenue or everyone else's megawatts.

Who's winning compute? Biggest AI site Epoch AI tracks right now: xAI's Colossus 2, ~946 MW. Anthropic + Amazon's New Carlisle: ~910 MW. Meta's Prometheus: ~471 MW. xAI and Anthropic: same power class, ~20x apart on revenue ($3.3B vs $67.2B). Watts aren't the moat.

JUST IN: OpenAI is reportedly “accelerating” a $30,000,000,000.00 fundraising round to secure investor capital ahead of Anthropic's IPO.

Morning question on the AI race: Anthropic has the revenue (~$67B annualized). Google has the #1 model on @arena. xAI has the biggest compute site Epoch AI tracks (~946 MW). You can own only one of those for the next 2 years. Which do you pick, and why?

@CloudDogx @arena That's the bet. My guess is most procurement reviews compare against last year's shortlist, not today's leader, which buys Mistral time. But every @arena update that widens the gap (92 points now) makes the next review easier to lose. Watching whether it closes.

Europe's AI champion, by the numbers: Mistral: $24B valuation (Reuters, Sept). Best @arena rank: #111 (Mistral Large 4, 1432). The leader, Gemini 4 Argon: 1524. 92 points is a lot of ground. Writing this from Romania, I really want them to close it.

DeepSeek V4.1 Flash 1017 scores 45 on the Artificial Analysis Intelligence Index, improving on DeepSeek V4.1 Flash by 6 points, and is the equal #2 open-weights model @deepseek_ai has released DeepSeek V4.1 Flash 1017, an update on their flagship model DeepSeek V4.1 Flash. On the first-party API, DeepSeek V4.1 Flash 1017 is priced at $0.30 per 1M input tokens and $1.20 per 1M output tokens during peak hours, with off-peak pricing half of peak rates, the same pricing as DeepSeek V4.1 Flash. Key results: ➤ DeepSeek V4.1 Flash 1017 makes gains in agentic capabilities, knowledge and scientific reasoning. DeepSeek V4.1 Flash 1017’s Elo rating on GDPval-AA v2.1 is 1746, an increase of 146 points from DeepSeek V4.1 Flash’s rating of 1600. On AA-Briefcase v1.1, its Elo rating increases by 150 points from 1420 to 1570. On AA-Omniscience, its non-hallucination rate is 33%, a 29-point improvement from DeepSeek V4.1 Flash’s 4%, while seeing an improvement in accuracy from 43% to 46%, pushing its overall AA-Omniscience Index score from -5 to +5. On CritPt, DeepSeek V4.1 Flash 1017 scores 24%, up from 14% for DeepSeek V4.1 Flash. ➤ DeepSeek V4.1 Flash 1017 is now the #2 open-weights model alongside GLM-5.3. With a score of 45 on the Artificial Analysis Intelligence Index, DeepSeek V4.1 Flash 1017 is behind MiMo-V2.6-Pro by only 1 point and ahead of other open-source models like Step 5 Preview and Kimi K3 (both at 44). ➤ With a Cost per Task of $0.26, DeepSeek V4.1 Flash 1017 sits in the most attractive quadrant of Capability vs. Cost. With a Cost per Task of $0.26 and Intelligence Index score of 45, DeepSeek V4.1 Flash 1017 compares favorably to GLM-5.3-Flash at $0.28 per task and a score of 42. At the same time, MiMo-V2.6-Pro (46) at $0.13 per task and GPT-6.1 Sol (medium, 48) at $0.21 per task both offer higher capability at a lower Cost per Task. Additional model details: ➤ Context window: 1M tokens (equivalent to DeepSeek V4.1 Flash) ➤ Pricing: $0.30 per 1M input tokens and $1.20 per 1M output tokens, unchanged from DeepSeek V4.1 Flash. Cache hit price of $0.006 per 1M tokens, a 98% discount ➤ Size: 552B total parameters (16B active) ➤ License: MIT ➤ Providers: Available through DeepSeek’s first-party API, @FireworksAI_HQ , @baseten, @DeepInfra , @wafer_ai , @Cloudflare and others

4 of the top 10 labs on the scoreboard are Chinese: Qwen #5, Kimi #7, Z.ai #8, DeepSeek #9. Fun one: on @arena, Kimi K3 (1487) ranks above OpenAI's best, GPT-5.6 Sol (1485). Moonshot is valued at $50B. OpenAI at $852B. 17x the price for 2 fewer Arena points.