NOUMENOpen app

Meta · Balanced

Muse Spark 1.1

Added Jul 9, 2026

Compare models

Choose up to 3 models to compare.1 of 3 chosen

Loading models…

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 45% of 465 models

Side by side

Muse Spark 1.1 compared

Specifications, prices, speed and benchmark scores next to each other. Benchmarks below show every compared model too.

Compare models

Choose up to 3 models to compare.1 of 3 chosen

Loading models…

Muse Spark 1.1MetaThis modelMuse Spark 1.3 ContributorMetaRemove
ProviderMetaMeta
Discovery tierBalancedEfficient
AddedJul 9, 2026Sep 2, 2026
Limits
Context window1M1.05MBest
Max output65.54K—
Average output460 tokens1.2K tokens
Pricing, USD per 1M tokens
Input$1.25$0.10Best
Output$4.25$0.20Best
Cache read$0.15$0.002Best
Performance
Throughput—145.4 tok/s
Time to first token—3.9 s
Request success (24h)—99.4%
Benchmark indexes
Intelligence Index33.7—
Coding Index71.3—
Capabilities
ReasoningYesYes
ToolsNoYes
VisionYesYes
Structured outputNoYes
PDF inputNoYes
Audio inputYesYes
Video inputYesYes
Reasoning effortminimal, low, medium, high, xhighminimal, low, medium, high, xhigh

Public evaluations

Benchmarks

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

  • Muse Spark 1.1
  • Muse Spark 1.3 Contributor

Intelligence Index

  • Muse Spark 1.133.7
  • Muse Spark 1.3 Contributor—

Muse Spark 1.1 tested at xhigh reasoning effort

Muse Spark 1.1: Better than 76% of 326 scored models

3.8Catalog models by score55.1

Indexes

  • Coding Index

    Composite of the coding evaluations

    • Muse Spark 1.1: 71.3
    • Muse Spark 1.3 Contributor: —

Agentic work

  • AutomationBench-AA

    Workflow automation, penalized for guardrail violations

    • Muse Spark 1.1: 38.8%
    • Muse Spark 1.3 Contributor: —
  • AutomationBench-AA tasks completed

    Workflows finished end to end without a guardrail violation

    • Muse Spark 1.1: 13.7%
    • Muse Spark 1.3 Contributor: —
  • AA-Briefcasev1.1

    Agentic knowledge work, rated head to head

    • Muse Spark 1.1: 850 Elo
    • Muse Spark 1.3 Contributor: —
  • GDPval-AAv2.1

    Economically valuable occupational tasks, rated head to head

    • Muse Spark 1.1: 1,211 Elo
    • Muse Spark 1.3 Contributor: —

Document reasoning

  • GDP.pdf

    Professional reasoning over PDF documents, all-pass rate

    • Muse Spark 1.1: 14.4%
    • Muse Spark 1.3 Contributor: —
  • AA-LCRv1.1

    Reasoning across long documents

    • Muse Spark 1.1: 77.7%
    • Muse Spark 1.3 Contributor: —
  • MLCR-AA

    Long-context reasoning over medical records

    • Muse Spark 1.1: 7.2%
    • Muse Spark 1.3 Contributor: —

Reasoning and knowledge

  • Humanity’s Last Exam

    Expert-level questions across academic fields

    • Muse Spark 1.1: 46.2%
    • Muse Spark 1.3 Contributor: —
  • GPQA Diamond

    Graduate-level science questions

    • Muse Spark 1.1: 89.8%
    • Muse Spark 1.3 Contributor: —

Coding

  • Terminal-Benchv4.0

    Practical software engineering in a terminal

    • Muse Spark 1.1: 6.1%
    • Muse Spark 1.3 Contributor: —
  • SciCode

    Scientific computing in Python

    • Muse Spark 1.1: 58.8%
    • Muse Spark 1.3 Contributor: —

Legacy evaluations

  • AA-LCR (unversioned)

    Long-context reasoning, earlier grading

    • Muse Spark 1.1: 77.7%
    • Muse Spark 1.3 Contributor: —

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

Other Meta models, starting with the same family.