Vedanuj Goswami

Today we are launching Muse Spark 1.1, an upgrade to muse spark 1 that greatly improves agentic, coding, multimodal, and computer use capabilities. We're also launching the Meta Model API in public preview. ai.meta.com/blog/introduci…

1/ muse spark 1.1 is an industry-competitive agentic and coding model. across many agentic evals it rivals gpt-5.5 and opus-4.8. available now through the new meta model api and in meta ai. 🧵

1/ releasing muse image today — the first image generation model from MSL. it's agentic: pairs with muse spark to reason through your prompt, search the web, and plan before it generates. people get what they meant on the first try. live now in the Meta AI app.

Excited to share what we’ve been building at Meta Superintelligence Labs! We just released Muse Spark, our first AI model. It's a natively multimodal reasoning model and the first step on our path to personal superintelligence. We've overhauled our entire stack to support scaling, and this is just the beginning. ai.meta.com/blog/introduci…

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. 🧵

Our first model from MSL, Muse Spark, is now available on meta.ai! This is an efficient all-rounder model. It supports fast responses, deeper thinking, visual chain of thought, a higher inference “Contemplating” mode. Plus, it’s natively multimodal. 1/

@giffmana @__kolesnikov__ @XiaohuaZhai Welcome to Meta!

hey all, couple quick notes: 1) yes, we will be joining Meta. 2) no, we did not get 100M sign-on, that's fake news. Excited about what's ahead though, will share more in due time! cc @__kolesnikov__ and @XiaohuaZhai.

We're glad to start getting Llama 4 in all your hands. We're already hearing lots of great results people are getting with these models. That said, we're also hearing some reports of mixed quality across different services. Since we dropped the models as soon as they were ready, we expect it'll take several days for all the public implementations to get dialed in. We'll keep working through our bug fixes and onboarding partners. We've also heard claims that we trained on test sets -- that's simply not true and we would never do that. Our best understanding is that the variable quality people are seeing is due to needing to stabilize implementations. We believe the Llama 4 models are a significant advancement and we're looking forward to working with the community to unlock their value.

Llama3.2 models are here 🎉! We are releasing the multimodal and lightweight Llama models.

So excited for the open release of Llama 3.1 405B - with MMLU > 87, it's a really strong model and I can't wait to see what you all build with it! llama.meta.com Also check out the paper here, with lots of details on how this was made: tinyurl.com/2z2cpj8m

Llama3.1 is out model: llama.meta.com/llama-download… paper: ai.meta.com/research/publi…

Very excited to release the technical report and the model weights for the all 3 sizes of llama3 models. It has been exciting past 12 months. Really looking forward to the incredible research this will unlock from the community. Now on to llama4 🚀

as my other amazing teammates have already shared, check out our llama 3.1 paper here! lots of fun tidbits about the highs, lows, sweat, and tears that go into training LLMs lol ... onto llama 4!!! ai.meta.com/research/publi…

tldr; you can go a long way in pre-training by (1) curating amazing data, (2) using a lot of FLOPs, and (3) otherwise not screwing up. All three are harder than they sound, so read the paper... That said, I'm amazed by our progress since Llama 3 - expect big things from Llama 4!

This was monumental effort possible by a huge collaboration between GenAI and AI Infra teams at Meta AI. Thanks and congrats to everyone on this release. @NamanGoyal21 @ml_perception @edunov @Ahmad_Al_Dahle @soumithchintala @reducescatter @sharan0909

Reliability : Despite the complexity of training at 16k scale, we achieved >90% effective training time on average across 4 month of training. [snapshot of a 54 day training interruptions]

Llama3 405B is out with impressive performance across the board and 128k ctx length! Along with improved models for 8B and 70B. Blog : llama.meta.com/llama-download… Paper : ai.meta.com/research/publi… A short 🧵 on what went into scaling and training the largest compute Llama model yet