Code

DeepSeek-Coder

DeepSeek's coding model family: from small autocompletion models to the large MoE V2, which matched closed models in 2024. Later, coding moved into DeepSeek's general models.

Developer
DeepSeek, China
First release
Nov 2023
Latest release
Sep 2024
Sizes
1.3B – 236B-A21B
License
Commercial use with conditionsDeepSeek License (commercial use allowed, some uses prohibited); code under MIT
Russian
Not supported
Ready-made builds
GGUF, AWQ, GPTQ, MLX (Apple)
Running
Available in OllamaAlso runs without a GPU
Industries
Software development
Deploy on your server Hugging Face GitHub

What it does

  • Code autocompletion and generation
  • Translating code between programming languages
  • Finding bugs and explaining other people's code

Where it is used

IT departmentsProduct developmentLegacy system maintenance

Hardware requirements

LaptopLaptop or regular PC, up to 8 GB of VRAM — smaller versions
fits
1 GPUOne GPU with 16–80 GB — mid-size versions
fits
ClusterServer with several GPUs — flagship versions
fits

Versions

  1. DeepSeek-Coder-V2-Instruct-0724
  2. DeepSeek-Coder-V2 и V2-Lite
  3. DeepSeek-Coder 7B v1.5
  4. DeepSeek-Coder 1.3B / 6.7B / 33B

How to run it

With Ollama — the fastest wayInstall Ollama on your computer or server and find the model in its library by name. Good enough to try the model on your own tasks in one evening.Find it in the Ollama library
On your own serverWeights are downloaded from Hugging Face and served with vLLM (load and API) or llama.cpp (modest hardware). The model then runs in a closed network with no per-request fees.Hugging Face
How much hardware you needCalculate the VRAM for the model size, context length and number of concurrent requests.Open the hardware calculator

I can set this up end to end: pick the model size, deploy it on your server and connect it to your systems. Quantization compresses a model so it takes less video memory and runs on more modest hardware. Answers change slightly, so quality is checked on your own examples.

Frequently asked questions

Can DeepSeek-Coder be used in a commercial project?

With conditions. License: DeepSeek License (commercial use allowed, some uses prohibited); code under MIT. Restrictions vary — region, company revenue, attribution requirements. Have a lawyer check the terms before a commercial launch.

What hardware does DeepSeek-Coder need?

At minimum: Laptop or regular PC, up to 8 GB of VRAM — smaller versions. Some versions also run on an ordinary CPU, without a GPU. You can calculate the exact VRAM for your model size and context in the hardware calculator.

Does DeepSeek-Coder support Russian?

No. The model card lists its languages and Russian is not among them.

Where can I download DeepSeek-Coder and what does it cost?

The DeepSeek-Coder weights are open and free to download. You only pay for the hardware it runs on and for the setup. Source links are at the bottom of this page.

How I deploy it for clients

  1. SelectionI pick the model size for your task and hardware and test it on your examples.
  2. DeploymentI deploy it on your server or in a closed network and provide an API.
  3. Fine-tuningI fine-tune it on your data (LoRA) or connect a knowledge base — whichever is cheaper for the task.
  4. IntegrationI connect it to your CRM, ERP, bot, website or team chat and set up monitoring.

Comparisons

Similar models

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DetailsTextDeepSeekDeepSeek · ChinaCommercial use allowed

DeepSeek's flagship line: from the first 7B/67B to V4-Pro with 1.6 trillion parameters. Closed-model quality under an open MIT license; V4-Flash-Vision-Exp and V4.1-Flash understand images, context up to 1M tokens.

DetailsCodeCode LlamaMeta · USACommercial use with conditions

A version of Llama 2 further trained on code, with variants for Python and for chat. Outdated, but many ready-made fine-tuned versions and tools exist.

Details

Source: huggingface.co/deepseek-ai/DeepSeek-Coder-V2-Instruct-0724. Data checked against the model card on 22 Sep 2026. Have a lawyer review the license before commercial launch.