Muse Spark 1.2 is Meta’s multimodal reasoning model for tool-assisted coding and agent workflows, with Standard API pricing and a 1M-token context.
Pricing conditions: Standard mode costs $1.25/M input, $0.15/M cached input and $4.25/M output, without a long-context premium. The separate muse-spark-1.2-contributor ID costs $0.10/M input, $0.002/M cached input and $0.20/M output and permits training on supplied content. 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 1.2 serves coding and tool-assisted agent work. Version 1.2 is the previous Spark revision and remains relevant when audio understanding matters. 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. Contributor mode is a separate route with discounted usage in exchange for training rights over supplied content. It must be selected deliberately; its price is not the Standard price. 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 1.2 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.
These records share a directory category. Check the source card, output type and deployment requirements before treating a model as a replacement.
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