Muse Spark 1.2
Muse Spark 1.2 is a reasoning model from Meta, designed for complex agentic tasks. It accepts text, images, video, audio, and PDF documents, returns text, and offers a 1M-token context...
Updated 5 h ago · first seen 11 Sept 2026
model_01M294WVSFKNWSHPA510330VFN
Overview
Identity
Identity block not returned by the API for this entity.
Openness
Openness not classified yet — no sourced evidence to place this model in the ontology.
Key facts
- Release date
Source:OpenRouter public model & pricing listingT2observed 12 h agomedium
- Openrouter id
Source:OpenRouter public model & pricing listingT2observed 12 h agomedium
Capabilities
Modalities
- Modalities
- audioimagetextvideo
- Input
- audioimagetextvideo
- Output
- text
Capabilities
Tool calling
Yes
OpenRouter public model & pricing listing · T2
Structured output
Yes
OpenRouter public model & pricing listing · T2
Reasoning
Yes
OpenRouter public model & pricing listing · T2
Vision
Yes
OpenRouter public model & pricing listing · T2
Audio
Unavailable
Fine-tuning available
Unavailable
- Context window
Source:OpenRouter public model & pricing listingT2observed 12 h agomedium
- Max output
Source:OpenRouter public model & pricing listingT2observed 12 h agomedium
Benchmarks14
Compare with another model →Comparable same task and conditions · Partially comparable same task, conditions differ (effort, temperature, judge) · Not comparable different variant or metric
No benchmark results recorded
Providers & Pricing1
All offers in the price terminal →USD per 1M tokens as published by each provider (USD). Rows are append-only: every change is kept in the history below.
Price history
Output price · USD / 1M tokens 1 provider
- OpenRouter
- OpenRouterfirst observed $4.2511 Sept 2026
Input price · USD / 1M tokens 1 provider
- OpenRouter
- OpenRouterfirst observed $1.2511 Sept 2026
Timeline16
Full timeline →Muse Spark 1.2 scores 74.325% on LiveBench
livebench_leaderboardMuse Spark 1.2 scores 78.575% on LiveBench
livebench_leaderboardMuse Spark 1.2 scores 76.458% on LiveBench
livebench_leaderboardMuse Spark 1.2 scores 91.203% on LiveBench
livebench_leaderboardMuse Spark 1.2 scores 57.576% on LiveBench
livebench_leaderboardMuse Spark 1.2 scores 77.541% on LiveBench
livebench_leaderboardMuse Spark 1.2 scores 90.005% on LiveBench
livebench_leaderboardMuse Spark 1.2 scores 77.955% on LiveBench
livebench_leaderboardMuse Spark 1.2 scores 80.15% on Terminal-Bench
artificial_analysisMuse Spark 1.2 scores 7.07% on Terminal-Bench
artificial_analysisMuse Spark 1.2 scores 57.41% on SciCode
artificial_analysisMuse Spark 1.2 scores 45.46% on Humanity's Last Exam
artificial_analysisMuse Spark 1.2 scores 39.8 on Artificial Analysis Intelligence Index
artificial_analysisOpenRouter lists Muse Spark 1.2 at $1.25 in / $4.25 out per 1M tokens
openrouter
Change history16
Viewing AI Atlas as of 12 Aug 2026 — attributes exactly as the atlas knew them on that day; later corrections are not shown.
Back to today →Muse Spark 1.2 was not yet in AI Atlas on 12 Aug 2026
Release daterelease_date1
Opennessopenness1
Context windowcontext_length1
Max outputmax_output_tokens1
Modalitiesmodalities1
Input modalitiesmodalities_input1
Output modalitiesmodalities_output1
Descriptiondescription1
File inputfile_input1
Aa median output tokens per secondmetric.aa_median_output_tokens_per_second1
Openrouter idopenrouter_id1
Reasoningreasoning1
Structured outputstructured_output1
Supported parameterssupported_parameters1
Tool callingtool_calling1
Visionvision1
Claims are temporal and append-only: a new observation closes the previous claim (valid_to) instead of overwriting it. Conflicting claims from different sources are kept side by side and flagged — never averaged. Methodology →
Provenance
Attributed facts
17
Source tiers
T217
Freshest observation
5 h ago
Conflicts
None
Source documents 3
Tier 1 = official/primary, 2 = quality secondary, 3 = community, 4 = unverified. Every snapshot is archived; see all sources and the methodology.
Data quality (56/100) measures how well AI Atlas knows this entity — completeness, primary-source ratio, freshness, conflicts — never how good the model is. Methodology →