Run a private AI coding assistant on your own hardware without sending code to external servers.
Complete code functions and fill in gaps across Python, JavaScript, Rust, Go, Java, C++, SQL, and 70+ other languages.
Build IDE plugins or editor integrations that understand multi-file project context for smarter suggestions.
Requires downloading large model weights from Hugging Face and sufficient GPU/CPU memory to run inference.
DeepSeek Coder is a family of AI models trained specifically to write, complete, and understand code. Unlike general-purpose AI, these models were built almost entirely on code, 87% of their training data is source code from a huge variety of programming languages (over 80 are supported, including Python, JavaScript, TypeScript, Rust, Go, Java, C++, SQL, and many more). The models come in different sizes, 1 billion, 5.7 billion, 6.7 billion, and 33 billion parameters, so you can pick one that fits your available computing resources. Smaller models run faster on less powerful hardware; the 33B model is more capable but needs a GPU with more memory. You can use DeepSeek Coder in three main ways: code completion (you give it a partial function and it finishes it), code insertion (you leave a gap in the middle of code and it fills it in), and chat-style interaction (you describe what you want in plain English and it writes the code). The models understand project-level context, not just single files, because they were trained with a large 16K token window. You would use this when you want a self-hosted AI coding assistant, meaning the model runs on your own machine or server rather than sending your code to a third-party cloud. It is built on Python and integrates with the Hugging Face ecosystem for downloading and running models.
Generated 2026-05-18 · Model: sonnet-4-6 · Verify against the repo before relying on details.