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Meta released Muse Spark 1.2 contributor tier, a reasoning model designed for developers at lower cost, accepting text, images, video, audio, and PDFs with a 1M-token context window. The model supports multi-agent workflows, structured output, parallel function calling, and configurable reasoning effort, performing well on multi-file refactors and extended debugging.

Muse Spark 1.2 contributor tier is a reasoning model from Meta designed for developers who want to start building at an even lower cost. It’s meaningfully cheaper than Muse Spark 1.2. Your prompts and outputs may be used to improve Meta’s products, making it ideal for experimentation, learning, and early-stage projects without worry about spend. It is a reasoning model from Meta, tailored for complex agentic tasks. It accepts text, images, video, audio, and PDF documents, returns text, and offers a 1M-token context window. The model is built to support multi-agent workflows, whether as either a main agent that plans and delegates or as a subagent executing in parallel. It works across multiple coding harnesses and supports structured output, parallel function calling, and configurable reasoning effort. In Meta’s testing, it performs well on multi-file refactors, extended debugging sessions, whole-repository generation, and tasks that stretch well past a single prompt.