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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 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.

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Muse Spark 1.1MetaThis modelDeepSeek V4 Flash Vision ExpDeepSeekRemove
ProviderMetaDeepSeek
Discovery tierBalancedEfficient
AddedJul 9, 2026Aug 21, 2026
Limits
Context window1M1.05MBest
Max output65.54K384KBest
Average output460 tokens1.3K tokens
Pricing, USD per 1M tokens
Input$1.25$0.22Best
Output$4.25$0.65Best
Cache read$0.15$0.0069Best
Performance
Throughput—141.3 tok/s
Time to first token—2.6 s
Request success (24h)—99.7%
Benchmark indexes
Intelligence Index33.734.3Best
Coding Index71.3Best69.1
Capabilities
ReasoningYesYes
ToolsNoYes
VisionYesYes
Structured outputNoYes
Audio inputYesNo
Video inputYesNo
Reasoning effortminimal, low, medium, high, xhighnone, low, high, max

Public evaluations

Benchmarks

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

  • Muse Spark 1.1
  • DeepSeek V4 Flash Vision Exp

Intelligence Index

  • Muse Spark 1.133.7
  • DeepSeek V4 Flash Vision Exp34.3

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: 71.3Top
    • DeepSeek V4 Flash Vision Exp: 69.1

Agentic work

  • AutomationBench-AA

    Workflow automation, penalized for guardrail violations

    • Muse Spark 1.1: 38.8%
    • DeepSeek V4 Flash Vision Exp: 54.0%Top

  • AutomationBench-AA tasks completed

    Workflows finished end to end without a guardrail violation

    • Muse Spark 1.1: 13.7%
    • DeepSeek V4 Flash Vision Exp: 23.0%Top

  • AA-Briefcasev1.1

    Agentic knowledge work, rated head to head

    • Muse Spark 1.1: 850 Elo
    • DeepSeek V4 Flash Vision Exp: 1,257 EloTop

  • GDPval-AAv2.1

    Economically valuable occupational tasks, rated head to head

    • Muse Spark 1.1: 1,211 Elo
    • DeepSeek V4 Flash Vision Exp: 1,433 EloTop

Document reasoning

  • GDP.pdf

    Professional reasoning over PDF documents, all-pass rate

    • Muse Spark 1.1: 14.4%Top
    • DeepSeek V4 Flash Vision Exp: 11.0%

  • AA-LCRv1.1

    Reasoning across long documents

    • Muse Spark 1.1: 77.7%
    • DeepSeek V4 Flash Vision Exp: 79.7%Top

  • MLCR-AA

    Long-context reasoning over medical records

    • Muse Spark 1.1: 7.2%
    • DeepSeek V4 Flash Vision Exp: —

Reasoning and knowledge

  • Humanity’s Last Exam

    Expert-level questions across academic fields

    • Muse Spark 1.1: 46.2%Top
    • DeepSeek V4 Flash Vision Exp: 38.6%

  • GPQA Diamond

    Graduate-level science questions

    • Muse Spark 1.1: 89.8%
    • DeepSeek V4 Flash Vision Exp: 90.8%Top

Coding

  • Terminal-Benchv4.0

    Practical software engineering in a terminal

    • Muse Spark 1.1: 6.1%
    • DeepSeek V4 Flash Vision Exp: 12.1%Top

  • SciCode

    Scientific computing in Python

    • Muse Spark 1.1: 58.8%Top
    • DeepSeek V4 Flash Vision Exp: 50.3%

Legacy evaluations

  • AA-LCR (unversioned)

    Long-context reasoning, earlier grading

    • Muse Spark 1.1: 77.7%
    • DeepSeek V4 Flash Vision Exp: 79.7%Top

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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