Model summary
Performance
Muse Ember (Max) is amongst the leading models in intelligence and well priced when comparing to other models of similar price. The model supports text and image input, outputs text, and has a 1M tokens context window.
Muse Ember (Max) scores 36 on the Artificial Analysis Intelligence Index, placing it well above average among comparable models (median: 24). When evaluating the Intelligence Index, it generated 115M tokens, which is somewhat verbose in comparison to the median of 97.1M.
Pricing for Muse Ember (Max) is $0.10 per 1M input tokens (competitively priced, median: $0.23) and $0.50 per 1M output tokens (competitively priced, median: $0.83). On average, it costs $0.14 per task to evaluate Muse Ember (Max) on the Intelligence Index.
| Reasoning | Yes This page shows the reasoning version of this model. A non-reasoning variant may also exist. |
|---|---|
| Input modality | Supports: text and image |
| Output modality | Supports: text |
| Context window | 1M ~1573 A4 pages of size 12 Arial font |
Metrics are compared against models of the same class:
- Non-reasoning models → compared only with other non-reasoning models
- Reasoning models → compared across both reasoning and non-reasoning
- Open weights models → compared only with other open weights models of the same size class:
- Tiny: ≤4B parameters
- Small: 4B–40B parameters
- Medium: 40B–150B parameters
- Large: >150B parameters
-
Proprietary models → compared across proprietary and open weights models of the same price range, using a blended 3:1 input/output price ratio:
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<$0.15 per 1M tokens
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$0.15–$1 per 1M tokens
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$1 per 1M tokens
Time per Task
Intelligence #
Artificial Analysis Intelligence Index
Artificial Analysis Intelligence Index by Open Weights / Proprietary
Intelligence Index vs. Cost per Task
Measures the performance of models on specific capabilities and industries
Artificial Analysis Finance & Accounting Index
Evaluations
Agentic knowledge work, Elo
Knowledge
1 - hallucination rate
Agentic SaaS workflows
Agentic scientific research workflows in a terminal
Agentic software engineering in open-source repositories
Reasoning & knowledge
Professional document reasoning, All-pass
Agentic coding & terminal use
Physics reasoning
Quantitative analysis on spreadsheets & documents
Legal agentic work, Hallucination-Gated All-Pass Rate
Agentic business operations
Agentic real-world work tasks, Elo
Agentic interactive 3D experiences, Elo
Product and brand videos designed in code, Elo
Kubernetes incident root-cause analysis
Medical long context reasoning
Visual reasoning
Rich, varied, well-crafted language
Well-structured, scannable, answer-first
Truthful, acknowledges uncertainty, non-sycophantic
Use of filler and generic language
AA-Briefcase v1.1
AA-Briefcase Elo
AA-Omniscience v1.1
AA-Omniscience Net Score
Token Use #
Output Tokens per Intelligence Index Task
Cost #
Cost per Intelligence Index Task
Cost to Run Artificial Analysis Intelligence Index
Pricing: Cache Hit, Input, and Output
Context Window #
Context Window
Frequently Asked Questions #
Common questions about Muse Ember (Max) Muse Ember (Max) was released on November 9, 2026.
Muse Ember (Max) was created by Meta. Muse Ember (Max) scores 36 on the Artificial Analysis Intelligence Index, placing it well above average among other models in a similar price tier (median: 24).
Muse Ember (Max) costs $0.10 per 1M input tokens (very competitive, median: $0.23) and $0.50 per 1M output tokens (very competitive, median: $0.83), based on the median across providers serving the model.
Muse Ember (Max) costs $0.10 per 1M input tokens and $0.50 per 1M output tokens (based on the median across providers serving the model). For a blended rate (7:2:1 cache hit/input/output ratio), this is $0.0728 per 1M tokens. Pricing may vary by provider. Compare provider pricing
When evaluated on the Intelligence Index, Muse Ember (Max) generated 115M output tokens, which is somewhat higher than average compared to other models in a similar price tier (median: 97.1M).
Yes, Muse Ember (Max) is a reasoning model. It uses extended thinking or chain-of-thought reasoning to work through complex problems before providing an answer.
Muse Ember (Max) supports text and image input.
Muse Ember (Max) supports text output. Yes, Muse Ember (Max) supports image input and can analyze, describe, and answer questions about images.
Yes, Muse Ember (Max) is multimodal. It can process text and image input and generate text output.
Muse Ember (Max) has a context window of 1M tokens. This determines how much text and conversation history the model can process in a single request.
No, Muse Ember (Max) is proprietary. The model weights are not publicly available.
Muse Ember (Max) is a proprietary model and Meta has not disclosed the model size or parameter count.
Muse Ember (Max) achieves a score of 36 on the Artificial Analysis Intelligence Index. This composite benchmark evaluates models across knowledge work, coding, science, and general knowledge.
Yes, Muse Ember (Max) is available via API through 1 provider. [Compare API providers](https://artificialanalysis.ai/models/muse-ember/providers)
Muse Ember (Max) is available through 1 API provider. [Compare providers](https://artificialanalysis.ai/models/muse-ember/providers)