Meta has launched Muse Code, a beta terminal-based AI coding agent, and Muse Spark 1.2, an updated frontier model for coding tasks. This release positions Meta directly against competitors like Anthropic and OpenAI in the AI coding assistant market. Muse Code functions as a comprehensive tool that can handle complete software engineering projects within large codebases, including planning, coding, and validation. Unlike many rivals, Muse Code utilizes persistent background agents to reduce latency and avoid redundant information gathering per task. For larger jobs, it employs parallel sub-agents working in isolated worktrees to protect the user's main project. An auditability feature logs all actions locally, ensuring tasks can be resumed precisely if interrupted. Muse Spark 1.2, the model powering Muse Code, has been specifically enhanced for coding through scaled-up training and co-training with Muse Code itself. In benchmarks, Muse Spark 1.2 shows strong performance, though it trails behind Anthropic's Claude Code in some evaluations. Meta offers Muse Spark 1.2 via its Meta Model API with two pricing tiers: a standard tier where data is not used for training, and a significantly cheaper "contributor" tier that allows Meta to use prompts and completions for model training. While the contributor tier offers a low-cost entry point, it requires a payment method and has stricter rate limits, making it suitable for individuals and experiments. Enterprises prioritizing code security will need to opt for the more expensive standard tier to prevent their data from being used for training. Meta's strategy with the contributor tier mirrors its historical approach of subsidizing access to gather data and improve its models.