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  1. Models
  2. Text
  3. Meta

Muse Spark Open

Built with Muse Spark Open. Meta's open-weight 816B-A42B model for coding and agentic workflows. Text and image input, text output, tool calling and structured output. Always reasons at low, medium, high, or xhigh effort. Custom Muse Model License and Usage Policy apply.

  • Reasoning
  • Vision
  • Tool Calling
  • Structured Output

Added Oct 15, 2026

Model weights

Pricing

Auto routing · per 1M tokens
Input
$1.25
Output
$4.25
Cache read
$0.15
Compare provider prices

Specifications

Context window
1M
Max output
N/A
Parameters
816B / 42B
Total / active

Benchmarks

Sourced from Artificial Analysis.

Intelligence Index

24.9

Intelligence Index: 24.9
Better than 39% of models compared

Agentic work

AutomationBench-AA

Workflow automation with guardrail penalties

49.7%

Better than 62% of models compared

AutomationBench-AA Tasks Completed

Fully completed workflows without guardrail violations

20.9%

Better than 66% of models compared

AA-Briefcase v1.1

Agentic knowledge work (Elo)

1278 Elo

Better than 66% of models compared

GDPval-AA v2.1

Economically valuable tasks (Elo)

1401 Elo

Better than 73% of models compared

Document reasoning

GDP.pdf

Professional PDF reasoning: all-pass rate

18.6%

Better than 66% of models compared

AA-LCR v1.1

Long context reasoning with updated grading

78.3%

Better than 79% of models compared

MLCR-AA

Medical long-context reasoning

7.8%

Better than 22% of models compared

Reasoning

HLE

Humanity's Last Exam

43.9%

Better than 92% of models compared

CritPt

Research-level physics reasoning

14.9%

Coding

Terminal-Bench v4.0

Practical coding and terminal tasks

8.1%

Better than 54% of models compared

SciCode

Python programming for scientific computing

58.4%

Better than 90% of models compared

Knowledge

AA-Omniscience Accuracy

Proportion of correctly answered questions

42.0%

AA-Omniscience Hallucination Rate

Rate of incorrect answers among non-correct responses

28.0%

Legacy benchmarks

GPQA Diamond (legacy)

Graduate-level scientific reasoning

89.0%

Better than 86% of models compared

AA-LCR (unversioned / legacy)

Long context reasoning evaluation

78.3%

Better than 79% of models compared

GDPval-AA (unversioned / legacy)

Economically valuable tasks

45.1%

Last updated Nov 4, 2026

Artificial Analysis

Providers

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Related text models

Compare Muse Spark Open with similar models from the same provider or model family.

Muse Spark 1.3

meta/muse-spark-1.3

Meta's Muse Spark 1.3 is a frontier multimodal reasoning model for long-horizon coding and agentic workflows, with strong gains in computer use, browsing, professional tool use, codebase understanding, instruction following, and million-token retrieval. It accepts text, images, audio, video, and files, supports tool calling and structured output, and always reasons before answering.

Muse Spark 1.3 Contributor

meta/muse-spark-1.3-contributor

Meta's Muse Spark 1.3 Contributor is a frontier multimodal reasoning model for long-horizon coding and agentic workflows, with strong gains in computer use, browsing, professional tool use, codebase understanding, and million-token retrieval. It accepts text, images, audio, video, and files, supports tool calling and structured output, and always reasons before answering. Prompts and outputs may be used by Meta for training and to improve its products.

Muse Spark 1.2

meta/muse-spark-1.2

Meta's Muse Spark 1.2 is a multimodal reasoning model for complex agentic and coding tasks, with tool calling, structured output, and a one-million-token context window.

Muse Spark 1.2 Contributor

meta/muse-spark-1.2-contributor

A much cheaper opt-in version of Muse Spark 1.2 with the same multimodal coding and agentic capabilities. Prompts and outputs sent to this Contributor model may be used by Meta for training and to improve its products; use the standard Muse Spark 1.2 model if you do not want your data used for training.

Muse Spark 1.1

meta/muse-spark-1.1

Meta's Muse Spark 1.1 is a long-context multimodal reasoning model served by the Meta Model API.

Muse Wonder

meta/muse-wonder

Meta's Muse Wonder is a frontier reasoning model designed for complex personal and professional agentic tasks. It accepts text, images, audio, video, and PDF documents across a one-million-token context window, supports tool calling and structured output, and always reasons before answering.