Exciting news: Muse Wonder Full (Max) by @AIatMeta has just debuted in the Code Arena: WebDev at #6# overall with 1726 pts, putting Meta in the top 3 labs! This is +75 pts and 11 places above Muse Wonder (Max) at #17# (1651 pts), and +67 pts and 8 places above Muse Spark 1.3 (Max) at #14# (1659 pts). Muse Wonder Full (#6#) also landed +16 pts above Claude Sonnet 5.5 (#17#), and +48 pts above Gemini 4 Argon (#10#). With this score, Muse took the #3# lab spot (previously held by Google). Across categories, Muse Wonder Full (Max) landed: - #4# in Data & Analytics and in Consumer Product - #5# in Brand & Marketing - #6# in Content Creation Tools - #7# in Gaming and in Simulations - #8# in Reference-Based Design Congrats to the @AIatMeta team and @alexandr_wang on this release!

The biggest gap between AI labs isn't whether their agents get the job done. It's whether users actually enjoy working with them. We tracked the best agent from @AnthropicAI, @OpenAI, @GoogleDeepMind, @Kimi_Moonshot, @SpaceXSI and @deepseek_ai across 4 key Agent Arena signals used between late June and the start of October to see how the industry is shifting. Three things stood out: 1. Users like some agents far more than others. On Praise vs Complaint, OpenAI and Anthropic sit at +35 points over the leaderboard average. Moonshot, xAI and DeepSeek land between +5 and +13. No other signal splits the labs this widely. 2. Agents are getting much better at delivery. On Confirmed Success, the average lab's best model went from -4 to +14 points in three months. Anthropic leads with Claude Opus 5.5 (Max) at +20. 3. Labs are converging on error recovery and steering. Since June, the spread between the six labs has more than halved on Bash Recovery (34 → 16 points) and nearly halved on Steerability (19 → 11). In short, the labs are catching up on avoiding failures. Leaving the user happy is where the top three are pulling away.

Results based on +5K real-world agentic sessions are in: Muse Wonder (Max) by @AIatMeta just landed in the Agent Arena at #12# with +6.4% net improvement. This result is +2.8 pts and four places above Muse Spark 1.3 (Max) at #16# with +3.6%. The added performance of Muse Wonder (Max) comes at a higher price: $1.13 median cost per task vs. $0.54 for Spark 1.3, or about 2.1× the cost. Compared with nearby models in Agent Arena, Muse Wonder (Max) shows cost efficiency: at $1.13/task, it comes within 1 percentage point of #10# GPT-5.6 Sol (xHigh) at 25% lower cost, and within 2pts of #9# Claude Fable 5 (High) at 67% lower cost. By category, Muse Wonder (Max) does better in Chat, Work and Code vs. Muse Spark 1.3: - Chat: #12# (+6.5%) vs. #15# (+3.3%) - Work: #13# (+6.8%) vs. #18# (+3.7%) - Code: #15# (+5.2%) vs. #18# (+4.2%) Congrats to the @AIatMeta team on this release!

Results based on +5K real-world agentic sessions are in: Muse Wonder (Max) by @AIatMeta just landed in the Agent Arena at #12# with +6.4% net improvement. This result is +2.8 pts and four places above Muse Spark 1.3 (Max) at #16# with +3.6%. The added performance of Muse Wonder (Max) comes at a higher price: $1.13 median cost per task vs. $0.54 for Spark 1.3, or about 2.1× the cost. Compared with nearby models in Agent Arena, Muse Wonder (Max) shows cost efficiency: at $1.13/task, it comes within 1 percentage point of #10# GPT-5.6 Sol (xHigh) at 25% lower cost, and within 2pts of #9# Claude Fable 5 (High) at 67% lower cost. By category, Muse Wonder (Max) does better in Chat, Work and Code vs. Muse Spark 1.3: - Chat: #12# (+6.5%) vs. #15# (+3.3%) - Work: #13# (+6.8%) vs. #18# (+3.7%) - Code: #15# (+5.2%) vs. #18# (+4.2%) Congrats to the @AIatMeta team on this release!

Max Spero, CEO of @pangram and one of TIME’s 100 most influential people in AI, just joined @petergostev to talk AI detection. @max_spero_ explains Pangram’s training process: synthetic mirrors, model-family fingerprints, AI-assisted writing, image detection and robustness against AI humanizers. They also cover how the team chooses base models, finds difficult training examples and builds the data and infrastructure to keep up with new AI models. Watch the full conversation in the thread.

Introducing our new agentic version of Max: Arena’s model router that achieves frontier-level performance at 37% lower cost. Built on 2.5M real-world agentic sessions from Agent Arena, Max learns to dynamically select the best model for each task, optimizing for both performance and cost. Max achieves a +14.7% net improvement score in Agent Arena at a median cost of $3.27 per task, matching the performance of Claude Fable 5.1 (Max) at 37% lower cost. Try Max today for a limited time, and dive into more technical details in the thread.

Muse Wonder (Max) by @AIatMeta has entered Code Arena: WebDev at #15# with 1651 pts and Text Arena at #2# with 1513 pts! In Code Arena: WebDev, Muse Wonder (Max) landed at #15# with 1651 pts. This result is slightly lower thanMuse Spark 1.3 (Max) at #12# with 1659 pts, within 4 pts of Kimi K3 (Max) at #14# with 1655 pts, and 11 pts above Grok 4.7 (xHigh) at #16# with 1640 pts. This release is a significant improvement over past Muse models in Text Arena. Compared with Muse Spark 1.3 (Max) at #11# with 1494 pts, Muse Wonder (Max) gained +19 pts and 9 places to #2#. It's 12 pts behind the #1-ranked# Gemini 4 Argon (High) with 1525 pts. Congrats to the @AIatMeta team on this release!

We’re offering direct access to our most intelligent variant of Max (Fable 5.1 + Astra) in Agent Mode for a limited time. Bring your most ambitious project and see what Max can do! Try Max today: We’ll also be releasing a version of Max via API in the future. If you’re interested in early access to Max via API, fill out the form at:

Introducing our new agentic version of Max: Arena’s model router that achieves frontier-level performance at 37% lower cost. Built on 2.5M real-world agentic sessions from Agent Arena, Max learns to dynamically select the best model for each task, optimizing for both performance and cost. Max achieves a +14.7% net improvement score in Agent Arena at a median cost of $3.27 per task, matching the performance of Claude Fable 5.1 (Max) at 37% lower cost. Try Max today for a limited time, and dive into more technical details in the thread.

Gemini 4 Argon by @GoogleDeepMind just went head-to-head with top frontier models across a set of generations. At 33% lower cost per task than GPT-6.1 Sol, and 70% lower than Claude Opus 5.5, see first impressions from @petergostev on how Gemini 4 Argon compares.

Watch @petergostev put Muse Wonder (Max) by @AIatMeta to the test across one-shot 3D scenes, animated HTML, and front-end designs. He compares it with Astra, Opus 5.5, GPT-6.1 Sol, Claude Sonnet 5.5, Fable, Kimi, and Mistral, and includes the cost of every generation. Arena scores for Muse Wonder are coming very soon. Stay tuned, and in the meantime see first impressions from @petergostev.

Arena CEO @ml_angelopoulos says using the wrong model is "so much worse than people realize." "People will literally be tipping their model $15 just by saying thank you at the end of the day."