LLM Reference

Muse Spark

Released
2026-04-08
Last refreshed
2026-05-14
Status
Researched 54d ago
ProprietaryCommercial use: unknownMultimodalCodingAgentsVisionJSON / Tool use

Muse Spark is a released coding, agents, and vision model; evaluate it while provider pricing coverage matures.

Use it for

  • Teams evaluating coding, agents, and vision

Do not use it for

  • Cost-sensitive launches that need sourced token pricing
  • Teams that need a tracked hosted API route today
Specifications
Family
Muse
Released
2026-04-08
Architecture
Decoder Only
Specialization
reasoning
Openness
Proprietary
Weights
Not released
Code
Unknown
Created by

Large-scale open-source AI for social technologies.

Menlo Park, California, United States
Founded 2013
Website
Pricing

No tracked provider token pricing is available yet.

About

Muse Spark is the first model in Meta's Muse family, developed by Meta Superintelligence Labs (MSL). It is a natively multimodal reasoning model with capabilities including tool-use, visual chain-of-thought reasoning, and multi-agent orchestration. Muse Spark achieves 58% on Humanity's Last Exam and 38% on FrontierScience Research benchmarks, while being competitive with Llama 4 Maverick at over 10x less compute. Available via meta.ai and the Meta AI app; private API preview only — not open-source.

Muse Spark is a proprietary model in the Muse family. The structured metadata tracks multimodal input, reasoning, function calling, and tool use. Headline tracked benchmarks include MMMU Pro 80.4, Chatbot Arena 1491.0, and Google-Proof Q&A 89.5.

Top use-case fit: coding, agents, and build tasks

Coding

1 relevant benchmark in the decision map.

Agents

1 relevant benchmark in the decision map.

Vision

Included by capability and metadata signals in the decision map.

Provider price ladder

No tracked provider token pricing is available for this model yet.

Capabilities

VisionMultimodalReasoningFunction CallingTool Use

Benchmark peer barsfor Coding

Benchmark scores(4)

Scores are benchmark-specific and are direction-aware: the same numeric gap can mean very different outcomes across suites. Use the leaderboard context and this model's provider route to decide whether the winning margin is meaningful for your workload.
BenchmarkScoreVersionSource
MMMU Pro80.4LLM-Stats aggregatorhttps://llm-stats.com/benchmarks/mmmu-pro
Chatbot Arena1491.0Arena Elohttps://arena.ai/leaderboard
Google-Proof Q&A89.5diamondhttps://datacamp.com/blog/muse-spark-review; https://labellerr.com/blog/muse-spark-benchmarks/
SWE-bench Verified77.4SWE-bench Verifiedhttps://benchlm.ai/benchmarks/sweVerified; https://llm-stats.com/benchmarks/swe-bench-verified

Migration checks

No linked migration route is available for this model yet.

Frequently asked questions

When was Muse Spark released?

Muse Spark was released on 2026-04-08.

What benchmarks has Muse Spark been tested on?

Muse Spark has been evaluated on 4 benchmarks, including MMMU Pro, Chatbot Arena, Google-Proof Q&A, SWE-bench Verified.