Muse Models by AI at Meta
1 model2026
About
Muse is Meta's family of natively multimodal reasoning models, developed by Meta Superintelligence Labs (MSL). Muse models are designed for complex reasoning tasks requiring integration of visual and textual inputs, with capabilities including tool-use, visual chain-of-thought, and multi-agent orchestration.
Current Variants
Use-when guidance is derived from seed capabilities, context, release, and replacement fields.
1 in view
Muse SparkCurrent
Use when the workload needs reasoning, tool use, and function calling.
2026-04reasoningtool usefunction calling
| Model | Use when | Released | Signals | Status |
|---|---|---|---|---|
| Muse Spark | Use when the workload needs reasoning, tool use, and function calling. | 2026-04 | reasoningtool usefunction calling | Current |
Release Timeline
1 release group2026-04
1 current
Muse Spark
Currentreasoningtool usefunction calling
Specifications(1 models)
| Model | Released | Vision | Multimodal | Reasoning | Fn Calling | Tool Use |
|---|---|---|---|---|---|---|
| Muse Spark | 2026-04 | Yes | Yes | Yes | Yes | Yes |
Frequently Asked Questions
- What is Muse used for?
- Muse is used for reasoning, vision and multimodal work, and agent workflows and tool use. The family description and listed model capabilities point to those workloads as the best fit.
- How does Muse compare to Chameleon?
- Muse by AI at Meta is strongest where you need reasoning, while Chameleon by AI at Meta is the closest related family to check for coding. Muse has 1 listed variant, while Chameleon reaches up to 4K context, so compare the specs and pricing tables before choosing a production model.
- Which Muse model should I use?
- If price is the main constraint, use the pricing table first because Muse does not have complete provider pricing in the local data. For the most capable/latest local choice, evaluate Muse Spark with reasoning, tool use, function calling, and multimodal inputs.
