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Meta · Balanced

Muse Spark 1.1

Added Jul 9, 2026

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Use in the app

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

  • Reasoning
  • Vision
  • Audio input
  • Video input
Input
Text, Images, Video, Audio
Output
Text
Reasoning effort
minimal · low · medium · high · xhigh
Discovery tier
Balanced

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
65.5K
Average output (7 days)
460 tokens
Longer than 46% of 473 models

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Public evaluations

Benchmarks

Independent evaluation results, with how each score ranks among the models in the Noumen catalog.

Intelligence Index

33.7

Tested at xhigh reasoning effort

Better than 76% of 326 scored models

3.8Catalog models by score55.1

Indexes

  • Coding Index

    71.3

    Composite of the coding evaluations

    Better than 78% of 168 scored models

Agentic work

  • AutomationBench-AA

    38.8%

    Workflow automation, penalized for guardrail violations

    Better than 56% of 173 scored models

  • AutomationBench-AA tasks completed

    13.7%

    Workflows finished end to end without a guardrail violation

    Better than 57% of 173 scored models

  • AA-Briefcasev1.1

    850 Elo

    Agentic knowledge work, rated head to head

    Better than 33% of 166 scored models

  • GDPval-AAv2.1

    1,211 Elo

    Economically valuable occupational tasks, rated head to head

    Better than 52% of 187 scored models

Document reasoning

  • GDP.pdf

    14.4%

    Professional reasoning over PDF documents, all-pass rate

    Better than 63% of 171 scored models

  • AA-LCRv1.1

    77.7%

    Reasoning across long documents

    Better than 64% of 309 scored models

  • MLCR-AA

    7.2%

    Long-context reasoning over medical records

    Better than 26% of 121 scored models

Reasoning and knowledge

  • Humanity’s Last Exam

    46.2%

    Expert-level questions across academic fields

    Better than 89% of 323 scored models

  • GPQA Diamond

    89.8%

    Graduate-level science questions

    Better than 78% of 291 scored models

Coding

  • Terminal-Benchv4.0

    6.1%

    Practical software engineering in a terminal

    Better than 56% of 171 scored models

  • SciCode

    58.8%

    Scientific computing in Python

    Better than 88% of 174 scored models

Legacy evaluations

  • AA-LCR (unversioned)

    77.7%

    Long-context reasoning, earlier grading

    Better than 64% of 309 scored models

Scores from Artificial Analysis, updated Oct 26, 2026. Muse Spark 1.1 was tested at xhigh reasoning effort; compare scores measured at the same effort.Artificial Analysis

Developers

Use it through the API

Noumen’s API is OpenAI-compatible: any Chat Completions client works with a base URL and a key.

Read the quickstart
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-1.1",
    "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-1.1",
    messages=[{"role": "user", "content": "Explain this stack trace."}],
)
print(reply.choices[0].message.content)

Meta

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