Muse Spark 1.1 is Meta’s multimodal reasoning model for tool-assisted coding and agent workflows, with Standard API pricing and a 1M-token context.
The specification score summarizes recorded features and limits. It is not a benchmark result.
Pricing conditions: Standard mode costs $1.25/M input, $0.15/M cached input and $4.25/M output, without a long-context premium. Version 1.1 has no Contributor variant and is not available in Muse Code. Search grounding costs $2.50 per 1,000 queries.
Recorded modality support shows what this model can accept and produce. An undocumented modality is shown as unknown rather than assumed to be unsupported.
Accepts
Produces
Muse Spark 1.1 serves coding and tool-assisted agent work. Version 1.1 is the original public API revision, introduced on 9 July 2026. It should not be confused with the initial unversioned Spark announcement in April. The model returns text within a 1,048,576-token context window.
The model accepts audio alongside text, images, video and PDFs and returns text. Tool calling and structured output support agent integrations. Keep the model ID explicit when reproducing a result, and verify the request format and reasoning settings against the selected version. A migration should replay actual tool schemas and include failed calls as well as successful responses.
The Standard route costs $1.25 per million input tokens and $4.25 per million output tokens, with cached input at $0.15. This version is available only in Standard mode on the API, rather than through Muse Code. Search queries are billed separately from generated text.
Build a small evaluation set from the work your application actually handles. Include incomplete information, contradictory inputs and a case that should stop for clarification. Define an acceptable deliverable before running the model, then inspect failures as carefully as successful examples. Keep input material, tools and effort settings consistent when comparing candidates.
Record the exact model identifier, deployment route and request settings with each result. Count complete runs, including rejected outputs, retries and tool calls. When the workflow creates files or code, open the files or execute the existing checks before accepting the result. A plausible first response can hide an incomplete final deliverable.
The specifications describe supported interfaces and request capacity. They do not establish a measured quality ranking or a latency guarantee for your account. SyncDev has not independently benchmarked this model. Choose a deployment after testing the languages, input formats and operating conditions that matter to your users.
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Compare the model on the work you need to complete.
Muse Spark 1.1 is listed for Audio-text-to-text, Image-text-to-text, Text generation, Video-text-to-text, Coding & Code Generation. It accepts text, image, video, audio, pdf and produces text. Use the publisher’s input format and preprocessing for your chosen deployment.
Documented limits: 1.05M context and 131.07K maximum output. The listed route has starting rates of $1.25 input and $4.25 output per million tokens. Measure a completed task using the prompts, documents and tools your application will use. Include reasoning and retries in the result.
Use the model identifier and account requirements for the selected API route. Confirm its request limits and output format with one complete task before connecting a larger workflow.
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