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Check exact model cardOpen weights where releasedUpdated August 2026

DeepSeek V3

DeepSeek V3 remains useful as a DeepSeek-family baseline for general chat, coding, and assistant workflows.

DeepSeek · DeepSeek

Editorial review

Reviewed byOpenSourcesAI EditorialLast updatedAugust 2026SourcesHugging Face model card (deepseek-ai/DeepSeek-V3)

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

General DeepSeek-family comparisons and assistant workflow evaluation.

Who should use it

  • General DeepSeek-family comparisons and assistant workflow evaluation.
  • Builders who want local or self-hosted testing options.
  • Developers evaluating coding assistant, repo-editing, and code review workflows.

Common workflows

  • General chat and coding baseline workflows
  • chat workflows
  • coding workflows
  • baseline workflows

Deployment and hardware notes

Local hardware needs vary by size, quantization, and runtime. Check the exact model card and serving stack.

License and usage notes

Check exact model card. Open weights where released. Verify the exact model card and license terms for the checkpoint or hosted provider you use.

Strengths

  • Open weights where released model option for DeepSeek workflows.
  • General DeepSeek-family comparisons and assistant workflow evaluation.
  • Use the exact checkpoint and quantization that matches your hardware and latency target.

Limitations

  • Verify license, deployment requirements, runtime support, and fit on your own workload before production use.
  • Local hardware needs vary by size, quantization, and runtime. Check the exact model card and serving stack.
  • 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

Use the exact checkpoint and quantization that matches your hardware and latency target.

Local runtimes: Ollama where supported, LM Studio where supported, llama.cpp where supported, Transformers

Platforms: Windows, macOS, Linux

Sources to verify

Hugging Face model card (deepseek-ai/DeepSeek-V3)

Related resources

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

DeepSeek family hubBest local LLM toolsPrivate local chatbot stackOllama + Open WebUI starter stackAI tools directory
Hardware~415 GB at Q4_K_M (684.5B total parameters, MoE) — server class, not a single-GPU modelRuntimeOllama or LM Studio where supported, llama.cpp, Transformers, vLLMContext163,840 tokens (RoPE-extended)Last updated2026
Hugging Face model card (deepseek-ai/DeepSeek-V3) →

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

Setup and deployment

What is quantization? GGUF, Q4, Q8 explained →RunPod — managed GPU cloud →Lambda Labs — A100 / H100 on demand →Vast.ai — crowdsourced GPU marketplace →

Related model pages

DeepSeek family hub →DeepSeek-V4-Pro →DeepSeek Coder 33B →DeepSeek Coder 6.7B →Gemma 2 27B Instruct →Gemma 2 9B Instruct →DeepSeek-R1 Distill 14B →

Guides, stacks, and comparisons

Best local LLM tools →Private local chatbot stack →Ollama + Open WebUI starter stack →Open-source AI coding assistants →Local coding assistant stack →Cursor vs Windsurf vs Cline →

Related models

DeepSeek-V4-ProTeams comparing frontier-style open-weight reasoning and coding models against hosted closed models.DeepSeek Coder 33BCoding-model comparisons and legacy baseline testing.DeepSeek Coder 6.7BLocal coding experiments and lightweight code generation baselines.Gemma 2 27B InstructEfficient local prototypes, app workflows, and Gemma-family comparisons.Gemma 2 9B InstructEfficient local prototypes, app workflows, and Gemma-family comparisons.DeepSeek-R1 Distill 14B14B open-weight model in the DeepSeek family.

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