Meta Launches Muse Spark 1.1: A Low-Cost, High-Performance Agentic Model

On July 9, Meta officially launched Muse Spark 1.1 (formerly Hornbill), a multimodal reasoning model. Upgraded from its first version, it focuses on strong agentic and coding capabilities at a low price, signaling Meta's return to the frontier AI race. The model is now accessible to developers via the public beta Meta Model API and Meta AI.

Core Capabilities and Technical Details

Muse Spark 1.1 features a 1 million token context and can compress history to retain essential steps. Meta highlighted improvements in tool use, computer use, coding, and multimodal understanding. It can zero-shot generalize to new tools, orchestrate multi-agent tasks, maintain context across apps, and process visual and audio inputs.

Benchmark Performance and Reactions

According to Alexandr Wang, the model achieved SOTA on benchmarks like Harvey Legal Bench and TaxEval. Its agentic capabilities rival GPT-5.5 and Opus-4.8, even outperforming Opus 4.8 and Grok 4.5 in some out-of-distribution evaluations. Both Garry Tan and Wang reported excellent real-world results using it on OpenClaw (robotics scenarios). Industry figures like Bindu Reddy also praised its benchmark performance and API availability.

Internal Use and Ecosystem Support

Meta stated that Muse Spark 1.1 is already used for internal coding and research workflows, automating model development. Externally, early adopters including Replit and Box have started building on the new API.

2026-07-09 ~ 2026-07-11 · 133 related posts

Full story(6 episodes)→

10 near-duplicate retellings: RihardJarc · shengjia_zhao · EverydayAI_ · ezyang · alexandr_wang · alexandr_wang · ren_hongyu · inductionheads · scaling01 · andrew_n_carr