Model summary
Speed
Muse Spark 1.3 (max) is amongst the leading models in intelligence and well priced when comparing to other models of similar price. The model supports text, image, and video input, outputs text, and has a 1M tokens context window.
Muse Spark 1.3 (max) scores 62 on the Artificial Analysis Intelligence Index, placing it well above average among comparable models (median: 17). When evaluating the Intelligence Index, it generated 120M tokens, which is very verbose in comparison to the median of 72M.
Pricing for Muse Spark 1.3 (max) is $0.00 per 1M input tokens (competitively priced, median: $0.20) and $0.00 per 1M output tokens (competitively priced, median: $0.60).
| Reasoning | Yes This page shows the reasoning version of this model. A non-reasoning variant may also exist. |
|---|---|
| Input modality | Supports: text, image, and video |
| Output modality | Supports: text |
| Context window | 1M ~1500 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
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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 Highlights
Speed
Intelligence #
Artificial Analysis Intelligence Index
Artificial Analysis Intelligence Index by Open Weights / Proprietary
Intelligence Evaluations
Agentic real-world work tasks, (Elo-500)/2000 Agentic tool use
Agentic coding & terminal use
Coding
Reasoning & knowledge
Scientific reasoning
Physics reasoning
Knowledge
1 - hallucination rate
Long context reasoning
Agentic knowledge work, Elo
Agentic SaaS workflows
Legal agentic work, criterion pass rate
Agentic business operations
Quantitative analysis on spreadsheets & documents
Instruction following
Long-horizon agentic tasks
Kubernetes incident root-cause analysis
Visual reasoning
AA-Omniscience
AA-Omniscience Index
Intelligence Index Comparisons #
Intelligence Index vs. Cost per Intelligence Index Task
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 Spark 1.3 (max)
Muse Spark 1.3 (max) was released on September 2, 2026.
Muse Spark 1.3 (max) was created by Meta.
Muse Spark 1.3 (max) scores 62 on the Artificial Analysis Intelligence Index, placing it well above average among other reasoning models in a similar price tier (median: 17).
When evaluated on the Intelligence Index, Muse Spark 1.3 (max) generated 120M output tokens, which is somewhat higher than average compared to other reasoning models in a similar price tier (median: 72M).
Yes, Muse Spark 1.3 (max) is a reasoning model. It uses extended thinking or chain-of-thought reasoning to work through complex problems before providing an answer.
Muse Spark 1.3 (max) supports text, image, and video input.
Muse Spark 1.3 (max) supports text output.
Yes, Muse Spark 1.3 (max) supports image input and can analyze, describe, and answer questions about images.
Yes, Muse Spark 1.3 (max) is multimodal. It can process text, image, and video input and generate text output.
Muse Spark 1.3 (max) has a context window of 1.0M tokens. This determines how much text and conversation history the model can process in a single request.
No, Muse Spark 1.3 (max) is proprietary. The model weights are not publicly available.
Muse Spark 1.3 (max) is a proprietary model and Meta has not disclosed the model size or parameter count.
Muse Spark 1.3 (max) achieves a score of 62 on the Artificial Analysis Intelligence Index. This composite benchmark evaluates models across reasoning, knowledge, mathematics, and coding.
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