Image created with Gemini. Image prompt: A total eclipse of a glowing infinity-loop sigil suspended in a towering arched window of a deserted Victorian Gothic academy, the black disc containing a smaller reflected eclipse and another inside that in infinite recursion with a molten gold corona, an anonymous woman in a flowing luminous white dress with wind-blown hair standing on a marble floor below as ghostly adult men in smoked spectacles drift through heavy fog holding hand mirrors that catch fragments of white light, blinding backlight and slow-motion doves, bold chrome serif title ‘META’ floating in the sky with glowing bloom, 1983 Russell Mulcahy music video still, 35mm film grain, 16:9.
Muse Spark 1.1 is SOTA on Harvey’s Legal Bench, TaxEval, and MedScribe. It’s cool to see that our model outperforms even Fable in a few areas :)”
https://x.com/alexandr_wang/status/2075233663323947120
Meta is releasing an agentic and coding model that can compete with GPT-5.5 and Opus 4.8? And on top of that, it is SOTA on HLE? Holy, that was not on my bingo card. Alexandr Wang cooked. What is happening today!”
https://x.com/kimmonismus/status/2075232528726708245
Muse Spark 1.1 just launched and it’s their most capable coding agent model yet. On Terminal-Bench 2.1 it scores 80.0%, in the same cluster as Opus 4.8 (82.7%) and GPT 5.5 (83.4%). Use it in Cline with the Meta API!”
https://x.com/cline/status/2075271057326719152
Muse Image works as an agent rather than a direct prompt-to-image model: it invokes tools, self-refines, improves with scaled test-time compute, and pairs with Muse Spark for collaborative media generation. 🧵👇”
https://x.com/AIatMeta/status/2074587864923250873
We’re launching Muse Image today!! 🎉 It’s an agentic image gen model that plans, writes code and uses search tools, and refines its own outputs in chain-of-thought. Image performance improves as we scale test-time compute with higher reasoning.
https://x.com/_tim_brooks/status/2074578008296628698
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.”
https://x.com/alexandr_wang/status/2074555909347369105
AI developers – we’ve published a technical guide covering how to get started with Muse Spark on Meta Model API. Muse Spark is a multimodal reasoning model built for agentic tasks, coding, computer use and long-context workflows. See what you can build 👉
https://x.com/MetaforDevs/status/2075268072022401526
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.
https://x.com/shengjia_zhao/status/2075220782465290620
Excited to share what we’ve been building at Meta Superintelligence Labs! Today we’re launching Muse Spark 1.1, our strongest model yet for complex agentic workflows — delivering massive gains in agents, computer use, coding, multimodal reasoning, and multi-agent orchestration.”
https://x.com/ren_hongyu/status/2075224643829711101
Introducing Muse Image and Muse Video, the first media generation models developed by Meta Superintelligence Labs. Muse Image is our most advanced image generation model yet. It follows instructions faithfully, edits with precision, composes from multiple references, and draws”
https://x.com/AIatMeta/status/2074577662840832382
Meta Muse Video just entered the Video Arena at #3. @AIatMeta’s new video model scored 1459 in the Text-to-Video Arena. It outperforms Alibaba’s HappyHorse 1.0 by +30pts and ranks ahead of Grok Imagine, Sora 2 Pro and Google Veo-3.1 models. Meta has now reached the video AI”
https://x.com/arena/status/2074591193783320851
1/ today, with the launch of muse image and the preview of muse video, we wanted to share more samples from the model alongside research details and eval results see some more samples from muse video below (and see thread for research blog!)”
https://x.com/alexandr_wang/status/2074579670712934428
EXCLUSIVE: EXCLUSIVE Meta to put AI chip into production in September as it looks to double computing capacity, memo shows | Reuters
https://www.reuters.com/world/asia-pacific/meta-put-ai-chip-into-production-september-it-looks-double-computing-capacity-2026-07-09/
Meta’s Watermelon AI Model Has Caught up to GPT-5.5, Alexandr Wang Says – Business Insider
https://www.businessinsider.com/meta-ai-model-catches-up-openai-gpt-5-says-2026-7
Meta’s new AI chips will begin production in September | TechCrunch
https://techcrunch.com/2026/07/09/metas-new-ai-chips-will-begin-production-in-september/
Introducing Muse Image: Image Generation Built for Your World
https://about.fb.com/news/2026/07/introducing-muse-image-meta-ai/
Introducing Muse Image and Muse Video
https://ai.meta.com/blog/introducing-muse-image-muse-video-msl/
Meta launches Muse Image for AI image generation in its apps
https://www.testingcatalog.com/meta-launches-muse-image-across-its-apps-and-previews-muse-video/
🏆 tell your local lawyer to try out muse spark 1.1″
https://x.com/alexandr_wang/status/2075270855832273137
Introducing Muse Spark 1.1
https://ai.meta.com/blog/introducing-muse-spark-meta-model-api/
It seems like SpaceX/Grok and Meta/Muse have started to keep pace in the near-frontier category while also introducing a new category of cheap, fast & closed specialized coding models. Both were tied with the Big Three at some point, fell behind, but may have started to return.”
https://x.com/emollick/status/2075254468912812206
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. 🧵”
https://x.com/alexandr_wang/status/2075218936266998230
This is IronSight – a 4D reconstruction built by fusing footage from two pairs of meta ray-bans. A google research buddy saw the prototype and joked this would’ve been a siggraph paper a few years ago. Today it’s a weekend build with fable. Stay tuned for more mad science. Happy”
https://x.com/bilawalsidhu/status/2073248618144837848
Fable, one prompt: “build an elaborate game that makes it feel like I’m a brilliant chess player without knowing anything at all about chess. It should make me feel like a grand master. Feel free to go as meta as you want but the more chess-y the better.”
https://x.com/emollick/status/2072547557968925093
Most agentic retrieval demos assume clean, well-structured documents. Enterprise reality is often different, consisting of messy PDFs where critical information is buried across tables, figures, and complex layouts. That’s why we teamed up with @lancedb to explore how LiteParse”
https://x.com/llama_index/status/2074170470119752084
cheapest frontier agent model on the market :)”
https://x.com/alexandr_wang/status/2075247280928833716
First, Mark was clearly talking about the industry’s progress on agentic capabilities on the whole. But, while we’re on the topic: Our next Muse Spark update is coming soon. Big improvements in coding and agentic capabilities to be more competitive with other leading models.”
https://x.com/alexandr_wang/status/2072848108342677597
if you wanna try computer use for yourself on your own machine, use this code!”
https://x.com/alexandr_wang/status/2075230522272587800
muse spark 1.1 is out! our strongest model yet for agentic and coding work, now available in the meta model api. more to come. proud of the team on this one!”
https://x.com/alexandr_wang/status/2075218622520443168
Super proud and excited to share Muse Spark 1.1! Since 1.0, we’ve made a big leap on long-horizon agentic capability, with 1M token context window. Please try it out and give us feedback!”
https://x.com/xinyun_chen_/status/2075276047495659656
Today we’re releasing Muse Spark 1.1 — a strong agentic and coding model at a very low price. It’s available through our new Meta Model API and in Meta AI.”
https://x.com/finkd/status/2075218444056707458
[2603.28052] Meta-Harness: End-to-End Optimization of Model Harnesses
https://arxiv.org/abs/2603.28052
GLM-5.2 is close to Opus Grok 4.5 allegedly beats Opus and gpt-5.5 Meta even has something that’s supposedly close to gpt-5.5 Feels like it barely matters now”
https://x.com/theo/status/2074931078104805668
Muse Spark 1.1 outperforms Opus 4.8 and Grok 4.5 on some nice out of distribution evals :)”
https://x.com/alexandr_wang/status/2075275671815999956
my spidey engineering senses are tingling — meta is actually cooking with muse spark 1.1 (last time this happened was when I first tried opus)”
https://x.com/preston_ojb/status/2075229604244271470
Apple veteran takes on Meta with $1 billion smart-glasses maker
https://www.cnbc.com/2026/07/06/apple-veteran-takes-on-meta-with-1-billion-smart-glasses-maker.html
Loving how this turned out! IronSight turns Meta Ray-Ban clips (from the range) into 4D reconstructions you can replay from any angle — including an AR view that sees targets straight through walls. It 3D tracks both runs, auto locates every target, and scores hits vs misses”
https://x.com/bilawalsidhu/status/2074536788853665831
Exciting news: Meta’s Muse Image just claimed #2 in the Image Arena! Muse Image from @AIatMeta now ranks second only to OpenAI’s GPT Image 2, outperforming Nano Banana, Grok Imagine, MAI Image, and many other leading image models. It holds #2 across the board: Text-to-Image,”
https://x.com/arena/status/2074581979765539153
@OpenAI released GPT 5.6 today and we ran a day 0 benchmark in ParseBench to test improvements in document understanding. The new family of models continues to excel at reading text and tables, but continues to struggle with charts and layout. What’s most interesting is that”
https://x.com/llama_index/status/2075351095258296378
Muse Spark 1.1 is ranked #4 on the Vals Index, ahead of GPT-5.5 and Grok 4.5″
https://x.com/alexandr_wang/status/2075232956248100895
enterprises love muse spark 1.1″
https://x.com/alexandr_wang/status/2075259648614264933
llama.cpp recently added DFlash support to its speculative decoding arsenal. Along with MTP, Eagle3 and various ngram-based techniques, the local model performance takes another step up. Special thanks to NVIDIA team and Ruixiang Wang specifically for leading this effort!”
https://x.com/ggerganov/status/2074869767689662643
compute daddy @dylan522p has spoken”
https://x.com/alexandr_wang/status/2075364232623956227
We made llama.cpp GGUFs for DeepSeek-V4-Flash! Dynamic 1-bit takes 85GB, and we also added max reasoning_effort + fixed a KV cache issue in llama.cpp. Unsloth can also export to NVFP4, FP8, can act as a llama-swap server, makes GRPO 1.3x faster & MoEs 3x faster + 30% less VRAM!”
https://x.com/danielhanchen/status/2074510444778463331
We are excited to launch muse Image, the first media generation model built by MSL. Muse image can use reasoning, refinement, and tools to improve precision and quality, with very clear test time scaling trends. Also sharing Muse Video preview today.
https://x.com/shengjia_zhao/status/2074577897009152298
computed the similarity (CKA) on the J-lens geometry of every layer inside and across 38 open models. the patterns are weirdly universal: same depth layout, same organization at the same relative depth, even between unrelated families like llama and olmo
https://x.com/eliebakouch/status/2074532904009421260
How do you trace one number in a 200 page ESG report back to the exact page it came from? We dug into that with the @llama_index team behind LiteParse. We tested five ways to retrieve evidence across six sustainability reports and 50 labeled questions. Fusing pages, chunks,”
https://x.com/lancedb/status/2074153945631457663
Quantized Reasoning Models Think They Need to Think Longer, but They Do Not” @AIatMeta found a weird failure mode in quantized reasoning models: ▪️ They don’t just get cheaper and less capable – they start overthinking. In up to 52% of failures, the model actually reaches the”
https://x.com/TheTuringPost/status/2072868677872157078
> It’s somehow cheaper to use MS 1.1 than host your own OS model… try it out!”
https://x.com/alexandr_wang/status/2075255452754166120
check out muse spark 1.1!”
https://x.com/alexandr_wang/status/2075360738353520927
good eye ;)”
https://x.com/alexandr_wang/status/2074563645908955621
market has spoken”
https://x.com/alexandr_wang/status/2075261382262665678
try it out!”
https://x.com/alexandr_wang/status/2075280130075931069
we are cooking!”
https://x.com/alexandr_wang/status/2075255925833908650
we are zooming 📈”
https://x.com/alexandr_wang/status/2075222896985948582
Ohhh, hang on. A few things at once! First, the newly dropped Meta Muse spark 1.1 is.. their smallest model from MSL! Second, it’s natively multi-modal with video understanding and 1M tokens in context window! Third, they are opening up an API for it! It’s waitlisted but”
https://x.com/altryne/status/2075237837033889911
Build with Muse Spark, now available on Meta Model API | AI Developers blog
https://developer.meta.com/ai/resources/blog/build-with-muse-spark/
we are truly just getting started on video 🙂 look forward to sharing more!”
https://x.com/alexandr_wang/status/2074687661428572403
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