Building useful coding agents takes more than generating code. Agents need to analyze an existing codebase, work across files and dependencies, use tools reliably, and keep making progress as a task evolves.
Muse Spark Open, a coding-optimized open-weight model from Meta, is available today in Microsoft Foundry Models through Hugging Face collection. Trained specifically for agentic coding workflows, Muse Spark Open combines a focus on first-attempt accuracy with reliable tool calling and deep codebase understanding, giving developers another option for building agents around the repositories they work in every day.
Built for the way developers work
Real development work spans debugging sessions, multi-file refactors, and changes that reach across an entire project. Muse Spark Open is trained on these workflows, with capabilities across code generation, debugging, and codebase understanding.
A 1M-token context window allows developers to bring extensive project context into a task, including legacy code, complex dependencies, and large collections of files. That broader context helps the model connect a local change to the surrounding codebase and reduces the need to split work into disconnected pieces. For teams building coding agents, this supports workflows such as investigating a bug across services, understanding an unfamiliar repository, or coordinating changes across multiple components. Learn more about this model.
Designed to sustain progress across complex tasks
Muse Spark Open is built to plan, act, observe results, and adjust its approach over extended workflows. Its training encompasses long-running tasks that require multiple steps, tools, and interactions across websites. With an appropriate agentic harness, Muse Spark Open can spawn and coordinate subagents for work that can be divided into separate tasks. It also supports web browsing, including multimodal browsing, and computer use across desktop, mobile, and browser environments. Separate commentary lets Muse Spark Open outputs a planned action before taking action, giving developers visibility into what the agent is doing and why as work progresses.
Understand more of the context behind the code
Software development draws on more than source files. Requirements arrive in documents, interfaces appear in screenshots, and issues may be captured in recordings. Muse Spark Open combines image and document understanding with audio and audio-video perception. As a reasoning model, it can work across what it sees, hears, and reads, creating opportunities for agents to connect these inputs with the code and tasks they support.
Open weights, more developer choice
Muse Spark Open is shared under the permissive Muse Model License with narrow commercial terms. Its open weights give developers flexibility to pursue cloud and on-premises deployments, as well as fine-tuning for specialized needs, subject to the license.
Availability through Hugging Face in Microsoft Foundry brings that choice into Foundry Models. Hugging Face models use a managed compute deployment path with dedicated GPU-backed inference endpoints, helping teams move from model discovery to integration with their applications.
Get started in Microsoft Foundry
Explore Muse Spark Open through the Hugging Face collection in Microsoft Foundry today and evaluate it against your own coding workflows. Start with the repositories, debugging tasks, and multi-file changes that matter to your team, then assess how the model performs within your agent’s tools and harness. Try it today Model Catalog | Microsoft Foundry.




