Muse Spark 1.2

Muse Spark 1.2 is Meta's coding-focused flagship model, released August 5, 2026 alongside Muse Code, a beta terminal coding agent. It significantly scales training compute on coding tasks and expands training environment diversity, improving code generation, complex debugging, codebase understanding, and end-to-end developer workflows. With a 1M context window, higher first-attempt accuracy, and more reliable tool calling, it is available today in Muse Code and through the Meta Model API with expanded global access.

Core Features

• Coding-focused training: Significantly scaled compute on coding tasks with broader environment diversity for code generation, debugging, and codebase understanding.
• 1M context: Long-running tasks run start to finish in one session without context splitting.
• Higher first-attempt accuracy: Optimized for real coding workflows with fewer failed attempts.
• Reliable tool calling: Built for agentic use with consistent function and tool invocation.
• Co-trained with Muse Code: Trained alongside the terminal agent using rejection-sampled harness trajectories, goals, compaction, and subagents for best harness compatibility.
• Dual tiers: muse-spark-1.2-contributor (used to improve Meta products) and muse-spark-1.2 (not used for product improvement).

Model Specifications

Use Cases

• Terminal coding agents: Muse Code uses Muse Spark 1.2 to build, debug, and ship code with multiple coordinating agents.
• Complex debugging: End-to-end developer workflows on large codebases.
• General agents: Maintains strength in general agent tasks alongside coding.
• Autonomous GitHub bots: Build GitHub agents on the Meta Model API with Muse Spark and OpenCode.

Advantages

1. Meta frontier coding: The model behind Muse Code, Meta's first terminal coding agent, benchmarked close to Claude Opus 5.
2. 1M context: Whole-repo, start-to-finish sessions in one call.
3. Harness-native: Co-trained with Muse Code's toolset for the best agent experience.

Tips

1. Pair with Muse Code for the intended harness integration; the model was co-trained with it.
2. Choose the non-contributor tier if you do not want your prompts used to improve Meta products.
3. Use the 1M context for whole-repo tasks to avoid manual context splitting.

Conclusion

Muse Spark 1.2 is Meta's answer to the coding-agent frontier: a 1M-context, coding-focused model co-trained with its own terminal agent. If you want Meta's frontier coding capability through a first-party harness or API, it is the flagship choice.