Reasoning

Check exact model cardOpen weights where releasedUpdated August 2026

DeepSeek R1 Distill Llama 70B

DeepSeek R1 Distill Llama 70B is a distilled DeepSeek R1 variant for reasoning evaluation with more accessible deployment options than the full model.

DeepSeek · DeepSeek

Editorial review

Reviewed byOpenSourcesAI EditorialLast updatedAugust 2026SourcesHugging Face model card (deepseek-ai/DeepSeek-R1-Distill-Llama-70B)

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

Reasoning experiments, local-friendly evaluation, and distilled model comparisons.

Who should use it

  • Reasoning experiments, local-friendly evaluation, and distilled model comparisons.
  • Builders who want local or self-hosted testing options.

Common workflows

  • Distilled reasoning and local evaluation
  • reasoning workflows
  • distilled workflows
  • local workflows
  • open weights 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.
  • Reasoning experiments, local-friendly evaluation, and distilled model comparisons.
  • 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: 131,072 tokens.
  • 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-R1-Distill-Llama-70B)

Related resources

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

DeepSeek family hubModel selection guideFrontier vs open-weight contextLocal coding assistant stackAI tools directory
Hardware~42.8 GB at Q4_K_M (70.6B parameters)RuntimeOllama or LM Studio where supported, llama.cpp, Transformers, vLLMContext131,072 tokensLast updated2026
Hugging Face model card (deepseek-ai/DeepSeek-R1-Distill-Llama-70B) →

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

Check if this model fits your GPU →What can 12GB 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 R1 Distill Llama 8B →DeepSeek R1 Distill Qwen 1.5B →DeepSeek R1 Distill Qwen 14B →DeepSeek-R1 Distill 14B →DeepSeek-R1 8B (0528 Qwen3) →DeepSeek Coder 33B →

Guides, stacks, and comparisons

Model selection guide →Frontier vs open-weight context →Local coding assistant stack →All model comparisons →

Related models

DeepSeek R1 Distill Llama 8BReasoning experiments, local-friendly evaluation, and distilled model comparisons.DeepSeek R1 Distill Qwen 1.5BReasoning experiments, local-friendly evaluation, and distilled model comparisons.DeepSeek R1 Distill Qwen 14BReasoning experiments, local-friendly evaluation, and distilled model comparisons.DeepSeek-R1 Distill 14B14B open-weight model in the DeepSeek family.DeepSeek-R1 8B (0528 Qwen3)8B open-weight model in the DeepSeek family.DeepSeek Coder 33BCoding-model comparisons and legacy baseline testing.

Ready to run this model locally?

Find a compatible interface in our Local AI Tools directory →