Code

DeepSeek LicenseOpen weightsUpdated August 2026Coding

DeepSeek Coder V2

Coding-specialized open model family worth testing for completion, refactoring, and coding assistant workflows.

DeepSeek · DeepSeek

Editorial review

Reviewed byOpenSourcesAI EditorialLast updatedAugust 2026SourcesHugging Face model card

Model checkpoints, context windows, provider support, local runtime compatibility, and license terms can change quickly. Verify the exact model card before production or commercial use.

Best for

Developers comparing open coding models for IDE assistants and coding agents.

Who should use it

  • Developers comparing open coding models for IDE assistants and coding agents.
  • Builders who want local or self-hosted testing options.
  • Developers evaluating coding assistant, repo-editing, and code review workflows.
  • Teams testing tool-use, agentic planning, and multi-step workflow behavior.

Common workflows

  • Code generation, code review, repository assistance
  • coding workflows
  • agents workflows
  • baseline workflows

Deployment and hardware notes

Large variants need serious GPU memory; use smaller or quantized builds for local tests.

License and usage notes

DeepSeek License. Open weights. Verify the exact model card and license terms for the checkpoint or hosted provider you use.

Strengths

  • Open weights model option for DeepSeek workflows.
  • Developers comparing open coding models for IDE assistants and coding agents.
  • Can be tested locally with smaller or quantized builds; larger variants need serious GPU memory.
  • Tracked as Coding in the OpenSourcesAI model directory.

Limitations

  • License and model size should be reviewed carefully for commercial deployments.
  • Large variants need serious GPU memory; use smaller or quantized builds for local tests.
  • Context window and limits: 163,840 tokens (RoPE-extended).
  • Verify the exact model card, provider docs, license, and serving support before production use.

Local workflow notes

Can be tested locally with smaller or quantized builds; larger variants need serious GPU memory.

Local runtimes: Ollama variants, vLLM, Transformers, llama.cpp community builds

Platforms: Windows, macOS, Linux, Workstations

Sources to verify

Hugging Face model card

Related resources

Continue with model source notes, local tools, and implementation guides related to this model.

DeepSeek family hubOpen-source AI coding assistantsLocal coding assistant stackCursor vs Windsurf vs ClineAI tools directory
Hardware24GB+ for smaller quantized variantsRuntimevLLM, Ollama variants, TransformersContext163,840 tokens (RoPE-extended)Last updated2026
Hugging Face model card →

Model ecosystem connections

Use these next-step links to move from this profile into related tools, comparisons, guides, stacks, and curated shortlists.

Recommended runtimes and tools

Ollama →llama.cpp →Transformers →vLLM →LM Studio →

Setup and deployment

Check if this model fits your GPU →What can 24GB VRAM run? →What is quantization? GGUF, Q4, Q8 explained →What is VRAM and how much do you need? →

Related model pages

DeepSeek family hub →DeepSeek Coder V2 Lite →DeepSeek R1 →DeepSeek R1 Distill Llama 70B →Devstral →DeepSeek-R1 Distill 14B →DeepSeek-R1 8B (0528 Qwen3) →

Guides, stacks, and comparisons

Open-source AI coding assistants →Local coding assistant stack →Cursor vs Windsurf vs Cline →What is MCP? →MCP security basics →Best MCP servers for AI agents →

Related models

DeepSeek Coder V2 LiteCoding assistant tests where full-size coder models are too heavy.DeepSeek R1Reasoning experiments, coding workflows, and evaluating open reasoning models against closed alternatives.DeepSeek R1 Distill Llama 70BReasoning experiments, local-friendly evaluation, and distilled model comparisons.DevstralDeveloper and coding workflow evaluationDeepSeek-R1 Distill 14B14B open-weight model in the DeepSeek family.DeepSeek-R1 8B (0528 Qwen3)8B open-weight model in the DeepSeek family.

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