DeepSeek R1 — Local AI Model by DeepSeek

作者： Jakub Rusinowski · 最后更新： 2025年1月20日

Superseded model. DeepSeek R1 has been superseded by DeepSeek V4.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 →

开源世界的最新轰动之作。DeepSeek R1采用混合专家架构（MoE），在推理和编程任务上媲美顶级专有模型。以出众的逻辑和数学能力著称。

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).

联盟营销声明: 本页部分链接为联盟推广链接——如果你通过它们购买，LLM Configurator 可能会获得佣金，而你无需支付任何额外费用。作为亚马逊联盟成员（Amazon Associate），LLM Configurator 会从符合条件的购买中获得收益。
Intel Arc B570 10GB
10 GB VRAM · 150 W board power
2026年价格波动较大——请以当前商品页价格为准。
在亚马逊查看价格

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?