This looks great. Can’t wait to give it a shot.

Meta is back! Muse Spark scores 52 on the Artificial Analysis Intelligence Index, behind only Gemini 3.1 Pro, GPT-5.4, and Claude Opus 4.6. Muse Spark is the first new release since Llama 4 in April 2025 and also Meta's first release that is not open weights Muse Spark is a new model from @Meta evaluated on Artificial Analysis. We were given early access by Meta to independently benchmark the model. It is the first frontier-class model from Meta since Llama 4 Maverick was released in April 2025, and notably the first @AIatMeta model that is not being released as open weights. The release follows Meta's reorganization of its AI efforts under Meta Superintelligence Labs, and signals that Meta is re-entering the frontier race after roughly a year of relative quiet. For context, Llama 4 Maverick and Scout scored 18 and 13 respectively on the Artificial Analysis Intelligence Index as non-reasoning models at the time of their release, while Muse Spark scores 52. Muse Spark essentially closes the gap between to the frontier in a single release. The model is not open source and is not yet accessible via an API but Meta has shared they expect this to come soon. Meta is also integrating Muse Spark into their first party products including their Meta AI chat product, Facebook, Instagram and Threads. Key takeaways from our benchmarks: ➤ Muse Spark scores 52 on the Artificial Analysis Intelligence Index, placing it within the top 5 models we have benchmarked. It sits ahead of Claude Sonnet 4.6, GLM-5.1, MiniMax-M2.7, Grok 4.20 and behind Gemini 3.1 Pro Preview, GPT-5.4 and Claude Opus 4.6 ➤ Muse Spark is notably token efficient for its intelligence level. It used 58M output tokens to run the Intelligence Index, comparable to Gemini 3.1 Pro Preview (57M) and notably lower than Claude Opus 4.6 (Adaptive Reasoning, max effort, 157M), GPT-5.4 (xhigh, 120M) and GLM-5 (110M) ➤ Muse Spark is the second-most capable vision model we have benchmarked. It scores 80.5% on MMMU-Pro, behind only Gemini 3.1 Pro Preview (82.4%) ➤ Muse Spark performs strongly on reasoning and instruction-following evaluations. It scores 39.9% on HLE, trailing only Gemini 3.1 Pro Preview (44.7%) and GPT-5.4 (xhigh, 41.6%). The model also achieved 5th highest in CritPT with a score of 11%, an eval that is focused on difficult physics research questions. This is substantially above above Gemini 3 Flash (9%) and Claude 4.6 Sonnet (3%) ➤ Agentic performance does not stand out. On GDPval-AA, our evalaution focused on real world work tasks, Muse Spark scores 1427, behind both Claude Sonnet 4.6 at 1648 and GPT-5.4 at 1676, but ahead of Gemini 3.1 Pro Preview at 1320. On On TerminalBench Hard, Muse Spark trails Claude Sonnet 4.6, GPT-5.4, and Gemini 3.1 Pro. Muse Spark joins others in achieving a high τ²-Bench Telecom score of 92% Key model details: ➤ Modalities: Multimodal including text and vision input, text output ➤ License: Proprietary, Meta's first frontier model not released as open weights ➤ Availability: No public API at the time of publishing. Meta expects to provide API access soon. Meta has started integration into their first party AI offering Meta AI and inside Facebook, Instagram, and Threads

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. 🧵

Recently tried a new app on my iPad called Bazaart (apps.apple.com/us/ap…). It came with a 3-day trial and 9.99/month or 83.99/year. I forgot to cancel and was just billed 83.99. What kind of an anti-customer dark pattern is this? Is it on Apple or on the dev @AppleSupport

A representative democracy tends to benefit everyone - not just members of one party. And it is the same whether it is the Republican or the Democrat party.

How I AI (2025 edition). #chatgpt #gemini #claude #metaai rangaprabhu.com/blog/how-i-u…

We are moving beyond single instruction following to genuine understanding and problem solving with Gemini Robotics 1.5. These models can now also think while acting, improving their generalization and transparency. You can read the 🤖🧠 now!

This is an incredible product and a preview of the future.

#Coolie is super fun. Enjoyed it. Total time pass. Thalaivar evergreen. Great supporting cast. @anirudhofficial music awesome. Solid plot from @Dir_Lokesh #CoolieReview #CoolieThePowerHouse

This is the current tsunami wave forecast arriving at 1150 PM PDT. Humboldt Co. is forecast to have a max. tsunami ~1 foot. Del Norte is forecast to have a max. wave height of 3-5 foot. People are advised to stay away from beaches, marinas, and harbors as many waves can arrive.

As much as I love my @WHOOP, I am glad there is now a class action lawsuit on their egregious renewal policy, easily one of the worst in the industry. As someone who was at the paying end of this scam, really hoping the extremely anti-consumer practice is killed. @willahmed

Maybe “Lauren” is growth hacking her way to YC’26 :) @ycombinator

AI Alliance has collaborated with Llama Stack as a foundational AI application framework designed to empower developers in building applications with ease and confidence. Read more in the post:

Oracle and Meta are delivering open, customizable AI—built for enterprise deployment. Join us on June 25 to explore how Llama models on OCI Generative AI can empower your teams to integrate, fine-tune, and securely deploy AI across any environment. Register now: bit.ly/4nagUe1

Congratulations to the winners of the Llama 4 NYC Hackathon! 🎉 🥇 1st Place - Pitch Perfect Perfect your public speaking with Live Llama feedback. Pitch perfect takes in your voice and filler words, body language and eye contact, as well as content and structure to coach you in real time. Check out the demo here. bit.ly/4mIKas0 Congrats to Yves Hughes! 🥈 2nd Place - AthletIQ AthletIQ analyzes your game footage and delivers personalized coaching insights to unlock your next level of performance. Check out the demo here. bit.ly/4kJ9WKX Congrats to Blake Moody, Lucas Roberts, Will Bryden, and Scott Williams! 🥉 3rd Place - Centaur SRE Centaur SRE automatically builds SRE's a bespoke dashboard on-the-fly in your observability platform to show you the metrics, traces, and logs you need to see first for an ongoing alert. Check out the demo here. bit.ly/4mMZG6w Congrats to Shah Ahmed! 🦙 Best use of Llama API - Parent Bridge ParentBridge uses AI to transform student assignments into personalized, bilingual progress reports that help parents understand exactly how their child is learning and how to support them at home. Check out the demo here. bit.ly/4kycvQg Congrats to Alexey Yakubov, Kyle Liao, and Shawnick Wang! 🗽NYC Impact Prize - MashaSquared MashaSquared created a web application that helps NYC residents get answers to their questions about city services in any language using AI. Check out the demo here. bit.ly/4mHJrHF Congrats to Masha Obaturova and Maryia Babinova! A huge thank you to all participants for their incredible projects and innovation! 🚀 Stay tuned for more hackathon footage coming soon! #Llama4NYCHackathon

Latest Meta Spatial SDK (v0.6.0) has been released! Some highlights: ✅ ISDK support ✅ New Android Studio plugin w templates ✅ Faster debugging w data model inspector ✅ Query filters & sorting ✅ GLTF animation pointers ✅ Perf & stability wins ✅ Spatial Editor v5.0

Future’s So Bright: Ray-Ban Meta Glasses Get New Styles & AI Updates meta.com/blog/ray-ban-ai-gla…

Catch our full GDC session with @c_pruett, Meta's Director of Games, as he shares insights into the past, present and future of developing VR and MR with Meta. ✨ Learn how the ecosystem is evolving and how user trends are shifting here 👉 bit.ly/4cwFCAm #MetaHorizon

1.5M tokens to website in 5 minutes 🙏 - Upload an entire repo of apps - Upload multiple sketches website - Use the repo content to populate the template Llama 4 supports 10M context upto 10 images in a session:

Llama 4 Intelligence Index Update: We have now replicated Meta’s claimed values for MMLU Pro and GPQA Diamond, pushing our Intelligence Index scores for both Scout and Maverick higher Key update details: ➤ We noted in our first post 48 hours ago that we noticed discrepancies between our measured results and Meta’s claimed scores for our multi-choice eval datasets (MMLU Pro and GPQA Diamond) ➤ After further experiments and and close review, we have decided that in accordance with our published principle against unfairly penalizing models where they get the content of questions correct but format answers differently, we will allow Llama 4’s answer style of ‘The best answer is A’ as legitimate answer for our multi-choice evals ➤ This leads to a jump in score for both Scout and Maverick (largest for Scout) in 2/7 of the evals that make up Artificial Analysis Intelligence Index, and therefore a jump in their Intelligence Index scores ➤ Scout’s Intelligence Index has moved from 36 to 43, and Maverick’s Intelligence Index has moved from 49 to 50. Overall, we continue to conclude that both Scout and Maverick are very impressive models and a significant contribution to the open weights AI ecosystem. While DeepSeek V3 0324 maintains a small lead over Maverick, we continue to note that Maverick has ~half the active parameters (17B vs 37B), and ~60% of the total parameters (402B vs 671B), while also supporting image inputs. All our tests have been performed on the Hugging Face release version of the Llama 4 weights for both Scout and Maverick, including testing via a range of third party cloud providers. None of our eval results are based on the experimental chat-tuned model provided to LMArena (Llama-4-Maverick-03-26-Experimental). We can also share that we have observed third party cloud APIs generally stabilizing over the last 48 hours. We will soon release endpoint-level comparison data to allow developers to understand whether any cloud providers are still serving versions of Llama 4 with accuracy issues.