Meta · language model
Muse Wonder: pricing, context and benchmarks
Muse Wonder is a language model from Meta released on October 12, 2026. It costs $4 per million input tokens and $20 per million output tokens, with a 1M-token context window. Epoch AI ranks it #12 of 125 rated models.
What you need to know about Muse Wonder
Muse Wonder was released by Meta (United States) on October 12, 2026. It accepts text, images, video, files, and audio as input and produces text. Its context window reaches 1,048,576 tokens, larger than 93 % of the models in the registry, and it can write up to 943,718 tokens in one go.
It is a recent model: real-world feedback and independent scores are still scarce.
Muse Wonder pricing
On OpenRouter, Muse Wonder costs $4 per million input tokens and $20 per million output tokens. Counting three tokens read for every token written, its average price is $8 per million, more expensive than 93 % of paid models (10.5 times the median of $0.76).
A concrete example: a task that sends 2,000 tokens (about 1,500 words) and receives a 500-token answer costs $0.018. At 1,000 tasks a day, budget $540 a month. The price calculator redoes this with your own volumes.
Tokens already sent and cached are billed at $0.2 per million.
Performance and benchmarks
The Epoch Capabilities Index (ECI), which aggregates published results across many benchmarks, gives Muse Wonder a score of 161.9 (range 159.4 to 165.4). That places it #12 of 125 rated models.
For at least equal performance, GPT-6.1 Sol, Gemini 4 Argon, and Claude Sonnet 5.5 cost at least 30% less.
Features, privacy and local use
- It supports tool calling, so it can drive an AI agent, call APIs or MCP servers.
- It can answer in an enforced JSON format (structured outputs).
- It is a reasoning model: it "thinks" before answering, which helps on hard tasks but uses more output tokens.
Its weights are not published: it can only be used through the Meta API or a broker such as OpenRouter, which means sending your data off your machines.
Other Meta models
| Model | Released | Avg. price | ECI |
|---|---|---|---|
| Muse Spark Open | Oct 15, 2026 | $2 | 155.1 |
| Muse Spark 1.3 | Sep 2, 2026 | $2 | 157.2 |
| Muse Spark 1.3 Contributor | Sep 2, 2026 | $0.13 | — |
| Muse Spark 1.2 Contributor | Aug 21, 2026 | $0.13 | — |
| Muse Glimmer 30B | Aug 9, 2026 | $0.53 | — |
| Muse Spark 1.2 | Aug 5, 2026 | $2 | 155.1 |
| Muse Spark 1.1 | Jul 16, 2026 | $2 | 154.1 |
Verdict
Muse Wonder scores 63/100 on our grid, which only uses published figures.
Strengths
- Among the top 20% of models according to Epoch AI (ECI 161.9).
- Very large context (1M tokens): long documents or a whole codebase fit in one request.
- Agent-ready: tool calling and structured JSON output.
Limitations
- Expensive: costlier than 93 % of paid models.
Avoid if…
- you process large volumes on a tight budget;
- your data must not leave your servers;
- your tasks are mostly simple: a non-reasoning model will cost less.
Alternatives
- GPT-5.6 Sol$8
- GPT-5.5$11.25
- GPT-5.6 Terra$4.5
- GPT-5.5 Pro$67.5
- GPT-5.4 Pro$67.5
- Claude Opus 5$10
Comparisons and tools
Learn more
Frequently asked questions
How much does Muse Wonder cost?
$4 per million input tokens and $20 per million output tokens on OpenRouter (checked October 25, 2026). A task with 2,000 tokens read and 500 written costs $0.018.
How big is Muse Wonder's context window?
1,048,576 tokens, roughly 786,000 words, with a maximum of 943,718 output tokens.
Can Muse Wonder run locally?
No, Meta does not publish its weights: it is API-only.
Is Muse Wonder suitable for an AI agent?
Technically yes: it supports tool calling and structured outputs. Then check its cost for your volume.
How good is Muse Wonder?
Epoch AI ranks it #12 of 125 rated models (ECI 161.9).
What are the alternatives to Muse Wonder?
The closest models on price and performance are GPT-5.6 Sol, GPT-5.5, and GPT-5.6 Terra.
Related articles
- Mistral AI: models, pricing and agentsOctober 25, 2026
- LLM benchmarks: how to read model rankingsOctober 24, 2026
- Running a local LLM: hardware, software, and limitationsOctober 24, 2026
- Open-source or closed models for your AI agents?October 5, 2026
Neutrality. No affiliate links. No vendor pays to be reviewed, rated or ranked. Reviews are directed by François Chollet, neutral and factual, and every data point is dated and sourced. How we score