DeepSeek Coder

Detailed overview

DeepSeek Coder is a family of open-source code language models (1B, 5.7B, 6.7B, and 33B parameters) trained from scratch on 2 trillion tokens, 87% code and 13% natural language in English and Chinese. Pretrained on project-level repositories with a 16K context window and a fill-in-the-blank objective, it supports both code completion and code infilling across an extensive range of programming languages, from Python and JavaScript to Rust, Verilog, and SQL. Developers integrate the models via Hugging Face Transformers, running them locally or on GPU infrastructure for tasks such as writing functions, completing partial code, and generating boilerplate for scripts, backend services, or command-line tools. The instruction-tuned 33B variant reportedly outperforms GPT-3.5-turbo on HumanEval and matches it on MBPP. Because it ships as raw model weights rather than a packaged IDE assistant, using it requires technical setup: installing dependencies, downloading model checkpoints, and provisioning suitable GPU hardware, with code and model released under separate licenses.

Pricing details

Open models are available to run or access through compatible providers; infrastructure costs may apply.