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Meta: Muse Spark 1.1

meta/muse-spark-1.1

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Muse Spark 1.1 is a multimodal reasoning model from Meta, built for agentic tasks. It accepts text, images, video, audio, and PDF documents and returns text, with a 1M-token context window.

The model is designed to orchestrate multi-agent workflows, acting as either a main agent that plans and delegates or as a subagent, and generalizes zero-shot to new tools, MCP servers, and custom skills. It supports structured output, parallel function calling, built-in search with citations, and configurable reasoning effort. Meta reports strong performance on real-world coding across large codebases, computer-use workflows, and visual-to-code generation.

Modalities

In / Out Price

$1.25 / $4.25per 1M

Context

1.0M

Released

Jul 16, 2026

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ProvidersPricingPerformanceUptimeBenchmarksAppsActivityFAQExplore

Providers

This model is hosted by one provider. OpenRouter forwards every request to it directly — no routing decisions to make.

Pricing

The average price customers actually pay for this model, next to the prices providers post. Caching and discounts mean the price actually paid is often well below the listed one.

Performance

Throughput is how fast the model writes (tokens per second — higher is better). Latency is total round-trip time (lower is better). TTFT is time-to-first-token — how long before you see anything appear (lower is better).

Uptime

Uptime is the percentage of the past 3 days that at least one provider was responding to requests. Availability is the percentage of time that inference was successfully served. OpenRouter continuously monitors and uses the next-best provider when one returns an error.

Benchmarks

Scores on standardized evaluations. Higher percentages are better — and rank percentile shows where this model lands among all models on OpenRouter.

Benchmark score summary for Meta: Muse Spark 1.1 (Artificial Analysis and Design Arena)
SourceBenchmarkScore
Artificial AnalysisMuse Spark 1.1 (xhigh) Intelligence Index34.3
Artificial AnalysisMuse Spark 1.1 (xhigh) Coding Index71.3
Artificial AnalysisMuse Spark 1.1 (xhigh) Agentic Index27.5
Artificial AnalysisMuse Spark 1.1 (xhigh) GPQA Diamond89.8%
Artificial AnalysisMuse Spark 1.1 (xhigh) HLE46.2%
Artificial AnalysisMuse Spark 1.1 (xhigh) AA-LCR77.7%
Artificial AnalysisMuse Spark 1.1 (xhigh) GDPval-AA39.7%
Artificial AnalysisMuse Spark 1.1 (xhigh) CritPt15.1%
Artificial AnalysisMuse Spark 1.1 (xhigh) SciCode58.8%
Artificial AnalysisMuse Spark 1.1 (xhigh) AA-Omniscience Accuracy52.0%
Artificial AnalysisMuse Spark 1.1 (xhigh) AA-Omniscience Non-Hallucination Rate50.0%
Design ArenaMuse Spark 1.1 Agents Arena Agenticgamedev Elo1183
Design ArenaMuse Spark 1.1 Agents Arena Androidnative Elo1189
Design ArenaMuse Spark 1.1 Agents Arena Full Stack Elo1212
Design ArenaMuse Spark 1.1 Agents Arena Godotgamedev Elo1141
Design ArenaMuse Spark 1.1 Agents Arena Htmlslides Elo1197
Design ArenaMuse Spark 1.1 Agents Arena Mobile Apps Elo1203
Design ArenaMuse Spark 1.1 Agents Arena Python-Pptxslides Elo1156
Design ArenaMuse Spark 1.1 Agents Arena Webapps Elo1217
Design ArenaMuse Spark 1.1 Models Arena 3D Elo1293
Design ArenaMuse Spark 1.1 Models Arena Asciiart Elo1301
Design ArenaMuse Spark 1.1 Models Arena Code Categories Elo1292
Design ArenaMuse Spark 1.1 Models Arena Data Visualization Elo1291
Design ArenaMuse Spark 1.1 Models Arena Game Development Elo1300
Design ArenaMuse Spark 1.1 Models Arena SVG Elo1278
Design ArenaMuse Spark 1.1 Models Arena UI Component Elo1308
Design ArenaMuse Spark 1.1 Models Arena Website Elo1282

Apps

Public apps that send the most traffic to this model. Good signal for what real production workloads look like — and a hint at which use cases this model is best suited for.

Activity

Token volume and request traffic to this model over time.

Quick Start

Drop-in code to call this model. OpenRouter's API is OpenAI-compatible — most SDKs work by just swapping the base URL. The only thing that changes between models is the model slug below.

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Frequently asked questions

Muse Spark 1.1 is a multimodal reasoning model from Meta, built for agentic tasks. It accepts text, images, video, audio, and PDF documents and returns text, with a 1M-token context window. The model is designed to orchestrate multi-agent workflows, acting as either a main agent that plans and delegates or as a subagent, and generalizes zero-shot to new tools, MCP servers, and custom skills.

Muse Spark 1.1 costs $1.25/M input tokens and $4.25/M output tokens, with separate rates for Cache Read at $0.15/M tokens and Web Search at $2.50/1K calls.

Muse Spark 1.1 has a 1,048,576 token context window.

Yes. Muse Spark 1.1 accepts tools and tool_choice for function calling. It also supports structured outputs via a JSON schema in response_format.

Muse Spark 1.1 accepts text, images, video, files such as PDFs and audio as input and returns text.

Muse Spark 1.3 Contributor, Muse Spark 1.3, Muse Spark 1.2 Contributor and 2 more are other text models from Meta.

Muse Spark 1.1 was released on July 16, 2026.