Song Jiang

Senior Research Engineer at Meta FAIR @AIatMeta | PhD from @UCLA

[Hongyu Ren @ren_hongyu]

Excited to share Muse Spark 1.2 and Muse Code (beta). Muse Spark 1.2 is an upgrade to 1.1 with overall improvements in coding and general agents. Muse Code is our harness designed for efficiently and robustly solving complex software engineering tasks. Try the bundle out!

https://t.co/WfzzTh4JLS

[Shengjia Zhao @shengjia_zhao]

An internal muse spark achieved a perfect score on APhO. Big congrats to the team, and thank you to the APhO committee!

[Alexandr Wang @alexandr_wang]

Muse Spark achieved a perfect score on the 2026 Asian Physics Olympiad!

Great milestone against our long-term goal of building AI systems to accelerate science.

[Artificial Analysis @ArtificialAnlys]

Muse Spark 1.1 (xhigh) scores 69 on the Artificial Analysis Coding Agent Index in the Opencode harness, offering a strong blend of performance and near frontier cost-efficiency

Muse Spark 1.1 lands just below GPT-5.5 (medium) in Codex (71) and ahead of Claude Opus 4.8 (medium) in Claude Code (67). Cost per task is among the lowest of frontier coding agents at ~$1.4, with the tradeoff of a higher time per task.

Congratulations @AIatMeta, @finkd, and @alexandr_wang on this result!

[Elaine Ya Le @ElaineYaLe6]

Super excited to bring Muse Spark 1.1 to the world! ✨✨✨

A solid agentic + coding + multimodal model, built to be really capable and incredibly affordable .

I’ll forever cherish the days and nights grinding with my incredibly talented and driven teammates. What an amazing team to build with!

Please try it out and let us know what you think! We’d love to hear your feedback. ❤️❤️❤️

[Hongyu Ren @ren_hongyu]

1.1 is a good agentic model

[Hongyu Ren @ren_hongyu]

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.

This is also our first API release! We’d love to hear your feedback.

And we’re just getting started, super proud of the team behind it, and the larger models are training right now. 🚀

https://t.co/GBoZgv2aA2

[Shengjia Zhao @shengjia_zhao]

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://t.co/Th9DzacJaW

[Alexandr Wang @alexandr_wang]

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. 🧵

[Song Jiang @songjiang24]

@tydsh Congratulations Yuandong!

[Guan-Horng Liu @guanhorng_liu]

I'm fortunate to have joined MuseSpark🥑 in its later stage. Seeing industrial, super-large-scale RL come alive has been a humbling and inspiring experience.

Distinct challenges emerge, and science has still proven critical.

Congrats to the team and many talented ppl at MSL🫡

[Jiawei Zhao @jiawzhao]

🥑🥑🥑Honored to work with our incredible team and many wonderful collaborators, on our first step toward personal superintelligence. Please try it out and let us know what you think!

[Elaine Ya Le @ElaineYaLe6]

Muse spark 🥑 is here!

9 months ago we started from scratch. Today we’ve rebuilt the entire stack and shipped a well-rounded, multimodal, and agent-native model.

This is just the beginning of a new era toward personal superintelligence. We’re early, but the momentum is real.

Give it a try at https://t.co/JYOXmerYWh — would love your feedback!

[Xiangning Chen @XiangningChen]

Very satisfying to see the beautiful RL scaling curves. It's a smart and token efficient model. Amazing team effort! 🚀

[Shengjia Zhao @shengjia_zhao]

Meta is back! Not only is it a high scoring models on AA third party eval, it is also one of the most token efficient.

[Ananya Kumar @ananyaku]

1/ It’s been so fun working with @shengjia_zhao, @alexandr_wang and the team to build muse spark from scratch. It is early and has rough edges, but excited to continue our research velocity. I especially love that we’re doubling down on the fundamental science. We’re focused on building methods that scale well along all axes: pretraining, RL, and test-time compute. https://t.co/tTQmEjUlTJ

[Hongyu Ren @ren_hongyu]

Check out Muse Spark, our first milestone in the quest for personal superintelligence! Scaling this with the team has been a total blast. Give it a spin and let us know what you think! 🥑

[Paria Rashidinejad @paria_rd]

I’ll be recruiting PhD students at USC ECE for Fall 2026! 🎓

Areas include:
• Reasoning, steering, editing, and few-shot learning in foundation models (LLMs, diffusion language models, VLAs, etc.)
• Reinforcement learning
• AI interpretability and safety
• Mathematical foundations of AI
• Your idea!💡

Submit your applications to USC ECE PhD program (the deadline is December 15, 2025): https://t.co/wMqsjGJ5CI

I’ll be at NeurIPS in San Diego. If you’re a prospective PhD student interested in these topics, come say hi and let’s chat about research opportunities at USC!

[Yuanhao Xiong @xiong_yuanhao]

Our team at Meta Superintelligence Labs is looking for summer research scientist interns to help shape the future of multimodal intelligence. Topics include multimodal reasoning, agents, and unified understanding & generation models.
https://t.co/Ln3DmFCcQj