DeepSeek R1 — Local AI Model by DeepSeek

Written by Jakub Rusinowski · Last updated January 20, 2025

Superseded model. DeepSeek R1 has been superseded by DeepSeek V4. This page is kept for reference; the newer family is a better starting point. View DeepSeek V4 →

DeepSeek R1 rivals proprietary top-tier models in reasoning and coding tasks using a Mixture-of-Experts architecture. Known for its exceptional logic and math capabilities. Previous generation — superseded by DeepSeek V4, which folds R1's reasoning strengths into a newer MoE architecture. Still widely deployed and supported.

Licence

LicenceWhat it permitsApplies to
MITCommercial use permitted
Commercial use permitted. No usage restrictions beyond attribution.
DeepSeek R1 Distill Llama 8B, DeepSeek R1 Distill Qwen 32B, DeepSeek R1 Distill Qwen 14B, DeepSeek R1 (671B)

Hardware Requirements

DeepSeek R1 Distill Llama 8BMin 6 GB VRAM · Q4_K_M · 128,000 ctx · ollama run deepseek-r1:8b
DeepSeek R1 Distill Qwen 32BMin 20 GB VRAM · Q4_K_M · 128,000 ctx · ollama run deepseek-r1:32b
DeepSeek R1 Distill Qwen 14BMin 9 GB VRAM · Q4_K_M · 128,000 ctx · ollama run deepseek-r1:14b
DeepSeek R1 (671B)Min 406 GB VRAM · Q4_K_M · 128,000 ctx · ollama run deepseek-r1:671b

Recommended GPU

The cheapest GPU that runs DeepSeek R1 locally (min 6 GB VRAM) is the Intel Arc B570 (10 GB).

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Intel Arc B570 10GB
10 GB VRAM · 150 W board power
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How to Run Locally

Install Ollama then run: ollama run deepseek-r1:8b

Minimum VRAM: 6 GB. For best results use Q4_K_M quantization.

DeepSeek R1 — Frequently Asked Questions

How much VRAM does DeepSeek R1 need?

DeepSeek R1 needs about 6 GB VRAM at Q4_K_M quantization for its smallest variant. Variants: DeepSeek R1 Distill Llama 8B (6 GB, Q4_K_M); DeepSeek R1 Distill Qwen 32B (20 GB, Q4_K_M); DeepSeek R1 Distill Qwen 14B (9 GB, Q4_K_M); DeepSeek R1 (671B) (406 GB, Q4_K_M). On Apple Silicon, unified memory counts toward this requirement.

Can I run DeepSeek R1 on an RTX 4090 (24 GB)?

Yes — DeepSeek R1 runs on an RTX 4090 (24 GB) and other 24 GB cards such as the RTX 3090. Smaller variants also fit comfortably on 8–16 GB GPUs at Q4_K_M.

What quantization should I use for DeepSeek R1?

Q4_K_M is the best balance of quality and VRAM for DeepSeek R1 in most cases. Choose Q8_0 for near-lossless quality if you have spare VRAM, or smaller quants (Q3/Q2) only when memory is tight.

How do I run DeepSeek R1 with Ollama?

Install Ollama, then run: ollama run deepseek-r1:8b. This downloads DeepSeek R1 and starts a local, OpenAI-compatible endpoint — no internet connection is needed after the initial download.

Can I Run DeepSeek R1 on My GPU?