Visual Coding at TBD @AIatMeta. https://xitter.cf/t.co/OUjOWWzAvd
Moon
Joined June 2021
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Yuning Mao retweeted
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!
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!
Yuning Mao retweeted
Muse Wonder, aka Watermelon is out today!! The consumer use cases of CUA are obvious from Muse, a particular use case I am super bullish about is verification.
CUA offers a feature-complete harness (GUI + code) for the agent to verify its creation, give itself feedback, and self-improve, aka CUA as verification.
This demo uses Muse Wonder to generate a globe web-app from a reference image and prompt. Two agents, same model: (a) a generation main agent, (b) a CUA verification sub-agent. They iterate until the CUA verifier is satisfied. This is an interesting test-time scaling with CUA.
As usual, work done with the incredible CUA and visual coding team at Meta MSL.
@taoyds, @yuning_pro, @EdwardSun0909
Yuning Mao retweeted
1/ we just publicly released Muse Spark 1.3 max!
we see significantly stronger coding and agentic performance on muse spark 1.3 max, so would strongly recommend trying it out even if you've already tried muse spark 1.3 high or muse spark 1.3 xhigh.
Yuning Mao retweeted
Muse Spark 1.3 Ultra Contributor vs Fable 5.1 xHigh Same prompt, both ran for roughly 2 hours
The prompt had a self improvement rule: if the independent judges scored the result below 9.5/10, it had to keep improving and try again,
What shocked me most was that Muse Spark just NEVER stopped, It went through 20 self improvement loops, launching 3 agents each time basically 60+ agent runs over 2 hours
And the cost?, Less than $1, Yes, under $1… in Ultra mode ,This completely exceeded my expectations Huge credit to Meta, this thing is a work of art
Yuning Mao retweeted
1/ today we’re releasing muse spark 1.3—available in muse code & the meta model api.
this is our most capable model yet—frontier performance almost too cheap to meter. much stronger at agentic and coding with better usability. we think users will really notice the jump.
Yuning Mao retweeted
Today we're also opening the weights for Muse Glimmer, a great 30B parameter dense model that can run locally. Soon we'll also release the weights for Muse Spark 1.2, our latest foundation model. Meta is a strong supporter of open source and I'm proud of these releases. Congrats to @alexandr_wang and the MSL team for all your great work on these models.
Yuning Mao retweeted
BREAKING: Muse Spark 1.1 takes 1st on our new Video to Website leaderboard with an Elo of 1250.
Video inputs capture richer context than static images - including interactions, transitions, and responsive behavior - challenging models to reproduce the full experience.
Only six labs currently support native video input, with @Meta debuting 14 Elo points ahead of @Kimi_Moonshot and 32 ahead of @GoogleDeepMind.
Video input is quickly becoming one of our users’ most requested capabilities.
Note: OpenAI & Anthropic currently do not yet support native video input in the API.
Congratulations to the @AIatMeta team!
Yuning Mao retweeted
meta just dropped a bomb.
Muse Spark 1.1 is 86% cheaper than GPT-5.6 Sol and 91% cheaper than Fable 5 on output tokens
($4.25 vs $30 vs $50 per M)
I thought the model was going to be horrendous, but it ended up being insanely fast, and very capable.
front end design is VERY strong.
Agentic capabilities seem great as it was able to spawn and even orchestrate other agents inside my app cnvs using the mcp and cli tool with zero instruction.
we have soo many insanely good models right now.
Yuning Mao retweeted
Grok 4.5 vs Meta Muse 1.1
I think both cooked really well!! WOW!
Left: Grok 4.5
Right: Meta Muse 1.1
Yuning Mao retweeted
Muse Spark debuts at #7 in the Code Arena - making @AIatMeta the #3 lab right behind @AnthropicAI’s Claude Sonnet 4.6 and @Zai_org’s GLM-5.1, surpassing Gemini-3.1-Pro and GPT-5.4.
Code Arena evaluates agentic coding on real-world tasks - building live websites and apps, ranked by users on real workflows. Huge congrats to @AIatMeta on this impressive milestone!
Introducing Muse Spark, the first in the Muse family of models developed by Meta Superintelligence Labs.
Muse Spark is a natively multimodal reasoning model with support for tool-use, visual chain of thought, and multi-agent orchestration.
Muse Spark is available today at meta.ai and the Meta AI app. We’re also making it available in private preview via API to select partners, and we hope to open-source future versions of the model.
Learn more: go.meta.me/43ea00
Yuning Mao retweeted
I tested Muse Spark with my nature-themed website oneshot test.
@alexandr_wang and team cooked
Prompt is below :)
Yuning Mao retweeted
After MORE THAN A YEAR, Meta finally released a model that passes the Hexagon Test and I’m not gonna lie this is weirdly emotional 🥹
sorry guys but history had to be documented!!
Introducing Muse Spark, the first in the Muse family of models developed by Meta Superintelligence Labs.
Muse Spark is a natively multimodal reasoning model with support for tool-use, visual chain of thought, and multi-agent orchestration.
Muse Spark is available today at meta.ai and the Meta AI app. We’re also making it available in private preview via API to select partners, and we hope to open-source future versions of the model.
Learn more: go.meta.me/43ea00
Yuning Mao retweeted
Cyberpunk robot SVG from a newly released Muse Spark from Meta.
Not bad 👀
BREAKING 🚨: Meta updated its Meta AI app with a slightly new design as well as its underlying model.
“I am Meta AI, powered by Muse Spark from the Muse model family.”
It constantly refers to the Muse model family and responses seem to be a bit different from earlier tested Avocado models.
Stealth launch 👀
Yuning Mao retweeted
The new model from Meta, Muse Spark, is pretty good at converting images to code!
Yuning Mao retweeted
1/ today we're releasing muse spark, the first model from MSL. nine months ago we rebuilt our ai stack from scratch. new infrastructure, new architecture, new data pipelines. muse spark is the result of that work, and now it powers meta ai. 🧵
Yuning Mao retweeted
Training on issue-solving only does NOT guarantee transfer to other tasks.
🎨Introducing Hybrid-Gym - synthetic training tasks for generalization (hybrid-gym.github.io)
+25.4% on SWE-Bench / +7.9% on SWT-Bench / +5.1% on Commit-0 with NO issue-solving / test-gen/... training
Yuning Mao retweeted
I was laid off by Meta today. As a Research Scientist, my work was just cited by the legendary @johnschulman2 and Nicholas Carlini yesterday.
I’m actively looking for new opportunities — please reach out if you have any openings!
