Meta · Frontier
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
- Tools
- Vision
- Structured output
- Input
- Text, Images
- Output
- Text
- Reasoning effort
- low · medium · high · xhigh
- Discovery tier
- Frontier
Pricing
USD per 1M tokens- Input
- $1.25
- Output
- $4.25
- Cache read
- $0.15
Reference prices as published by the model provider. API example
Specifications
- Context window
- 1M
- Max output
- —
- Average output (7 days)
- 1.3K tokens
- Longer than 80% of 473 models
Side by side
Compare models
Put Muse Spark Open next to up to three other models. The comparison stays in the link, so you can share it.
Public evaluations
Benchmarks
Independent evaluation results, with how each score ranks among the models in the Noumen catalog.
Intelligence Index
38.9
Tested at xhigh reasoning effort
Better than 83% of 326 scored models
Agentic work
AutomationBench-AA
49.7%Workflow automation, penalized for guardrail violations
Better than 64% of 173 scored models
AutomationBench-AA tasks completed
20.9%Workflows finished end to end without a guardrail violation
Better than 66% of 173 scored models
AA-Briefcasev1.1
1,279 EloAgentic knowledge work, rated head to head
Better than 67% of 166 scored models
GDPval-AAv2.1
1,401 EloEconomically valuable occupational tasks, rated head to head
Better than 64% of 187 scored models
Document reasoning
GDP.pdf
18.6%Professional reasoning over PDF documents, all-pass rate
Better than 73% of 171 scored models
AA-LCRv1.1
78.3%Reasoning across long documents
Better than 69% of 309 scored models
MLCR-AA
7.8%Long-context reasoning over medical records
Better than 28% of 121 scored models
Reasoning and knowledge
Humanity’s Last Exam
43.9%Expert-level questions across academic fields
Better than 86% of 323 scored models
GPQA Diamond
89.0%Graduate-level science questions
Better than 72% of 291 scored models
Coding
Terminal-Benchv4.0
8.1%Practical software engineering in a terminal
Better than 60% of 171 scored models
SciCode
58.4%Scientific computing in Python
Better than 85% of 174 scored models
Legacy evaluations
AA-LCR (unversioned)
78.3%Long-context reasoning, earlier grading
Better than 69% of 309 scored models
Scores from Artificial Analysis, updated Oct 26, 2026. Muse Spark Open was tested at xhigh reasoning effort; compare scores measured at the same effort.Artificial Analysis
- #15Website1306
Ranks among Noumen catalog models on Design Arena leaderboards. Only top-20 placements are listed.Design Arena
Live routing data
Performance and reliability
Recent averages across requests routed for this model. Your own speed depends on prompt length, reasoning effort and load.
- Prompt cache hits
- 0.0%
- About $1.25 per 1M input tokens with caching
Cache hits are the share of input tokens recently served from a prompt cache across all requests. They are not a forecast of your own hit rate.
Developers
Use it through the API
Noumen’s API is OpenAI-compatible: any Chat Completions client works with a base URL and a key.
curl https://www.noumen.xyz/api/v1/chat/completions \
-H "Authorization: Bearer $NOUMEN_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "meta/muse-spark-open",
"reasoning_effort": "medium",
"messages": [{ "role": "user", "content": "Explain this stack trace." }]
}'import os
from openai import OpenAI
client = OpenAI(base_url="https://www.noumen.xyz/api/v1", api_key=os.environ["NOUMEN_API_KEY"])
reply = client.chat.completions.create(
model="meta/muse-spark-open",
messages=[{"role": "user", "content": "Explain this stack trace."}],
)
print(reply.choices[0].message.content)Meta
Related models
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