@alexandr_wangOct 16

Known affiliation

after an exciting week of launches (muse wonder [full] & muse spark open), i want to write a note of appreciation to the amazing research teams at meta superintelligence labs on reaching such a special milestone ♥️ we started MSL and TBD a little more than a year ago and set a goal of producing a frontier model within a year or so. given where llama4 landed, that was an incredibly audacious goal, and we knew it wouldn't be easy. many people told us it would be impossible. we knew it was unlikely, but still worth doing. a remarkable group of researchers and engineers joined the effort from inside and outside meta. every single person came in, picked up a shovel, and got to work with earnestness and urgency. nobody asked whose job it was. we assembled a team of the most brilliant people i have ever had the opportunity to work with (and remember, i was an HRT intern 🙃). i am surrounded by ambitious, visionary, technically excellent, hard-working, pragmatic, thoughtful scientists, engineers, and product folks—people who will chase a weird loss spike past midnight just because they need to know why. these models are the product of their passion, hard work, and brilliance. somewhat paradoxically, when we started TBD, we set a principle of no deadlines. we knew we had an astronomical amount of work ahead of us—across pretraining, post-training, RL, multimodal, infrastructure, safety, data, AND frontier research. there was no use setting arbitrary timelines—we just had to get to work, be thoughtful, and build the foundations of a frontier research effort in record time. and run after run, this team did exactly that. our researchers are magicians. i can only describe building these models with this team as a wondrous journey of scientific discovery. i am constantly amazed by what we can accomplish with scaling. i will remember this past year for the rest of my life—the late nights, the broken runs, the evals that came back better than any of us dared to hope. watching this team create wonder after wonder has been a true and deep gift. more than just the models we released this week, we have built a machine that builds new models. it often sounds like a cop-out to say labs can just turn the crank to keep scaling, but now i have seen it first-hand. sure, it's a lot of work and a careful process, but we have built a scalable system to keep advancing at the frontier, and i am really proud of how fast this team keeps making these models better. lastly, i get to work with researchers who care deeply about how their work benefits humanity. it's easy to forget when everything is changing so fast, but the whole damn point is to make people's lives better. time and time again, i have seen our researchers, engineers, and product folks build our technology with care so it can truly be good for the world—whether that's building the best models for muse, thoughtfully open-sourcing strong models, or making sure the alignment and security of our systems are rock solid. this is a team of people who never forget there's a real person on the other side of every prompt. thank you to everyone at MSL for being part of this crazy journey over the past year. i'm so grateful for every one of you, and our work is not done!

@aakashguptaOct 16

Six months ago, Meta wouldn't let anyone outside the company download this AI. This morning they put it online for free so literally anyone can grab it, and they did it three days after building a better one. Pay attention to that order of events, because it's how Meta decides what to give away now. Back in April, Meta called Muse Spark the most powerful model it had ever made and kept the weights locked up. On Monday they launched Muse Wonder, which beats it. This morning all 816 billion parameters of Muse Spark went up on Hugging Face. So the rule at Meta seems pretty simple at this point. Something goes open source the week it stops being the best thing Meta sells. That's a big change from the Llama days. When Zuck released Llama 3.1 405B in 2024, it was the best model Meta had, and he wrote a whole letter about why open source was the future. Meta didn't sell AI back then, so giving it away cost them nothing and made OpenAI's product a little less special every time someone downloaded it. Fast forward to this week and Meta has an actual AI business. Muse Wonder runs $4 per million input tokens and $20 per million output, about what Anthropic charges for Claude Opus 5.5, and the top version, Wonder Full, isn't on the API at all. You have to pay for a Muse Code subscription to touch it. Now look at what they gave away. Meta's own benchmark chart has Kimi K3 beating Muse Spark Open on Terminal-Bench 2.1, 85.0 to 76.4, and GLM 5.3 and Qwen beat it there too. That's why the announcement says "most capable US open-weight model," with the US in there on purpose. Think about who actually wants this thing. It's the American company whose lawyers won't approve Chinese models and who's paying OpenAI or Anthropic for a mid-range model right now. Meta just handed that company a free version, which eats into the cheaper tier where its rivals make a lot of their money, and Meta's own paid model sits safely one step above it. Then there's Apple. The whole model runs on two Mac Studios with 512GB of memory each, a setup Apple won't even start selling until later this month. Zuck thanked Apple CEO John Ternus by name. In 2022, Apple's privacy changes cost Meta about $10 billion in ad revenue in one year. Both companies come out ahead when developers run AI on their own desks instead of renting it from OpenAI or Anthropic, and apparently that's enough to get two old rivals to share a launch day. My bet is Muse Wonder's weights show up right around the week Meta ships something that beats it.

@itsolelehmannOct 15

American open source is FLYING HIGH again 🇺🇸 Zuck this week: ships Muse Wonder, open-sources Muse Spark, and gets Apple to tweak its own software so the thing runs well on a Mac 18 months ago people were dunking on Llama 4's benchmarks. now Meta's open-source model beats Kimi K3, GLM 5.3 and Qwen on agent tool use and the hardest reasoning test (HLE). what a turnaround story Meta is right now

@alexfinnOct 15

America is SO back Zuck just announced Muse Spark Open is dropping later today, built with Mac Studios in mind This is bigger than you think The Meta Muse model was trained specifically for agent tasks. Now we can run it locally, plugged into agents like Hermes This is the future of AI Local, open weights models powering local open source harnesses running on our own hardware Completely personalized, custom intelligence with complete privacy 5 years from now very person on earth will have this. Their own custom digital worker getting tasks done for them 24/7 And the best part is, it's all American made baby🇺🇸 If you haven't gotten into local models yet. NOW is the time

@alexandr_wangOct 12

Known affiliation

MUSE WONDER this is the culmination of over a year of research and infrastructure work in msl since we originally shipped muse spark in april, we have continued to scale our models across pre-training and RL, now reaching the frontier 🏆 see our model's improvements on the artificial analysis index: