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Audio understanding in Muse Spark 1.3 is currently not fully supported, and response quality for requests including audio content may be degraded.

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Meta: Muse Spark 1.3

meta/muse-spark-1.3

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Muse Spark 1.3 is a multimodal reasoning model from Meta for long-running agentic, multi-agent, and coding workflows. It is designed to keep track of information across extended tasks, work through conflicting inputs, and request clarification or confirmation when needed, with an emphasis on concise execution.

Modalities

In / Out Price

$1.25 / $4.25per 1M

Context

1.0M

Released

Sep 2, 2026

Compare
BenchmarksProvidersPricingPerformanceUptimeAppsActivityFAQExplore

Benchmarks

Scores on standardized evaluations and this model’s own outputs on shared benchmark prompts. Higher percentages are better — and each rank shows where this model lands among the models evaluated on that source.

Benchmark score summary for Meta: Muse Spark 1.3 (Design Arena)
SourceBenchmarkScore
Design ArenaMuse Spark 1.3 (xhigh) Agents Arena Full Stack Elo1305
Design ArenaMuse Spark 1.3 (xhigh) Agents Arena Mobile Apps Elo1226
Design ArenaMuse Spark 1.3 (xhigh) Agents Arena Python-Pptxslides Elo1245
Design ArenaMuse Spark 1.3 (xhigh) Agents Arena Webapps Elo1300
Design ArenaMuse Spark 1.3 (xhigh) Models Arena 3D Elo1382
Design ArenaMuse Spark 1.3 (xhigh) Models Arena Code Categories Elo1363
Design ArenaMuse Spark 1.3 (xhigh) Models Arena Data Visualization Elo1344
Design ArenaMuse Spark 1.3 (xhigh) Models Arena Game Development Elo1356
Design ArenaMuse Spark 1.3 (xhigh) Models Arena SVG Elo1346
Design ArenaMuse Spark 1.3 (xhigh) Models Arena UI Component Elo1375
Design ArenaMuse Spark 1.3 (xhigh) Models Arena Website Elo1363

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.

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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$1.25$4.25$0.153.06s97 tps
100.00%

Throughput

97tok/s

P50, best across providers

Latency

3.06s

P50, best provider

Uptime (3d)The model was reachable. Request routed to a provider.

100.00%

Availability (3d)The model returned inference from any provider. Errors and empty responses count against it.

96.77%

Availability over the last 3 days

Last 72 hours
Availability 96.77%
3 Days Ago2 Days AgoYesterdayNow

Availability over the last 24 hours

OpenRouter Availability
98.23%

When an error occurs in an upstream provider, we can recover by routing to another healthy provider, if your request filters allow it. You can access per-provider uptime data programmatically through the Endpoints API. Learn more about our load balancing and customization options.

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Frequently asked questions

Muse Spark 1.3 is a multimodal reasoning model from Meta for long-running agentic, multi-agent, and coding workflows. It is designed to keep track of information across extended tasks, work through conflicting inputs, and request clarification or confirmation when needed, with an emphasis on concise execution.

Muse Spark 1.3 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 1.3 has a 1,048,576 token context window.

Yes. Muse Spark 1.3 accepts tools and tool_choice for function calling. It also supports structured outputs via a JSON schema in response_format.

Muse Spark 1.3 accepts text, images, video, files such as PDFs, and audio as input and returns text.

Muse Spark 1.3 Contributor, Muse Spark 1.2 Contributor, Muse Glimmer 30B and 2 more are other text models from Meta.

Muse Spark 1.3 was released on September 2, 2026.