Text model · DeepSeek-R1
DeepSeek R1: RAM and VRAM requirements
DeepSeek R1 needs about 383.7 GB to run at Q4_K_M (the Q4_K_M GGUF file is ~376.65 GB to download; KV cache and overhead add the rest), or about 671.3 GB at Q8_0. The lightest hardware that runs it is a high-memory machine.
DeepSeek-R1 family · 671B params (Mixture-of-Experts: activates only 37B of 671B params per token, so generation is faster than the total size suggests) · released Jan 2025.
Shopping for hardware? See what runs DeepSeek R1 →
Q4_K_M and Q8_0 are GGUF download (file) sizes. Memory @ Q4 includes the KV cache and overhead, so it runs larger than the file on disk.
Will it run on your device?
DeepSeek R1 runs on 0 of 40 tracked devices at Q4_K_M.
Memory breakdown
How context length changes it
Longer context grows the KV cache, which for DeepSeek R1 is sized by its 37B active params, not the full 671B. It needs ~383.7 GB at 4k and ~576.3 GB at 128k.
Benchmark scores
Sourced third-party benchmarks for the full-precision DeepSeek R1, not a specific quant. See the full leaderboard.
Quantization sizes
| Quantization | Size on disk |
|---|---|
| Q2_K | 281 GB est |
| Q3_K_M | 328 GB est |
| Q4_K_M (default) | 376.65 GB |
| Q5_K_M | 478.1 GB est |
| Q6_K | 550.2 GB est |
| Q8_0 | 664.3 GB |
| FP16 | 1342 GB est |
Lower quant = smaller and faster, slightly lower quality. Q4_K_M is the common default.
Run it
ollama run deepseek-r1:671b llama-cli -hf unsloth/DeepSeek-R1-GGUF:Q4_K_M lms get unsloth/DeepSeek-R1-GGUF Which devices can run DeepSeek R1?
Apple Silicon Macs
- Apple M1 (8GB) No
- Apple M2 (16GB) No
- Apple M4 (16GB) No
- Apple M5 (16GB) No
- Apple M3 Pro (18GB) No
- Apple M4 (24GB) No
- Apple M4 Pro (24GB) No
- Apple M5 (32GB) No
- Apple M4 Pro (48GB) No
- Apple M5 Pro (48GB) No
- Apple M4 Max (64GB) No
- Apple M4 Max (128GB) No
- Apple M5 Max (128GB) No
- Apple M3 Ultra (256GB) No
RAM-only laptops
iPhone & iPad
Android
NVIDIA GPUs
Same job, different size
Pick by what fits your memory: step down to free up VRAM, or step up if you have headroom.
Similar models
Head-to-head
FAQ
How much VRAM or RAM does DeepSeek R1 need?
At Q4_K_M, DeepSeek R1 needs about 383.7 GB (weights ~376.65 GB + KV cache + overhead) at a 4k context. At Q8_0 budget ~671.3 GB.
What is the Q4_K_M GGUF file size of DeepSeek R1?
The Q4_K_M GGUF file is about 376.65 GB to download, and the Q8_0 GGUF is about 664.3 GB. That is the weights file on disk; to run it you also need room for the KV cache and overhead, so budget ~383.7 GB of memory at Q4_K_M.
Can DeepSeek R1 run on a laptop?
DeepSeek R1 is large; you need a high-memory Mac or multi-GPU setup at Q4_K_M.
Is DeepSeek R1 cheaper to run because it is a MoE model?
It is faster, not lighter. DeepSeek R1 activates only 37B of 671B params per token (so it runs quickly), but all experts must stay in memory, so it still needs memory for the full 671B.
Can I use DeepSeek R1 commercially?
Yes. DeepSeek R1 is licensed MIT, which permits commercial use.
Understand the numbers
Short guides to the ideas behind DeepSeek R1's memory and quant figures.
DeepSeek R1, 671B sparse MoE (37B active). Q4_K_M is ~377GB across a 9-file series, beyond any consumer device. unsloth 1.58-bit dynamic quants run in ~140-160GB, so a 192GB Mac Studio can run it slowly. Size from the unsloth GGUF repo, cross-checked against the Ollama 671B tag.
Sources
Last validated 2026-08-03. Memory figures are estimates. See methodology.