Text model · DeepSeek-R1-Distill

DeepSeek-R1-Distill-Qwen 32B: RAM and VRAM requirements

DeepSeek-R1-Distill-Qwen 32B needs about 22.1 GB to run at Q4_K_M (the Q4_K_M GGUF file is ~19.85 GB to download; KV cache and overhead add the rest), or about 37 GB at Q8_0. The lightest hardware that runs it is Nvidia GeForce RTX 4090 (24GB).

DeepSeek-R1-Distill family · 32B params · released Jan 2025 · 79.3M Ollama pulls.

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License MIT · Commercial OK ↓ 801.4K/mo ♥ 1.6K on HuggingFace

Q4_K_M GGUF

19.85 GB

Q8_0 GGUF

34.82 GB

Memory @ Q4 (4k)

~22.1 GB

Context

128 k

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-Distill-Qwen 32B runs on 12 of 40 tracked devices at Q4_K_M.

9 run well 3 tight fit 28 too small

Fit check Q4_K_M

Your device

Apple M4 (16GB)

No, not enough memory

needs 22.1 GB usable 10.5 GB

See the full breakdown

Memory breakdown

Weights (Q4_K_M)19.85 GB

KV cache (4k)1.4 GB

Overhead0.8 GB

Total22.1 GB

How context length changes it

4k context ~22.1 GB 32k context ~31.6 GB 128k context ~64.1 GB

Longer context grows the KV cache quickly: DeepSeek-R1-Distill-Qwen 32B needs ~22.1 GB at 4k but ~64.1 GB at 128k, which can push it past a device that fits it at a short context.

Speed drops too: every token re-reads the KV cache, so at 128k context DeepSeek-R1-Distill-Qwen 32B generates at roughly ~31% of its short-context speed. How this is estimated.

Quantization sizes

GGUF quantson disk

Quantization	Size on disk
Q2_K	13.4 GB est
Q3_K_M	15.6 GB est
Q4_K_M (default)	19.85 GB
Q5_K_M	22.8 GB est
Q6_K	26.2 GB est
Q8_0	34.82 GB
FP16	64 GB est

Lower quant = smaller and faster, slightly lower quality. Q4_K_M is the common default.

Run it

Ollama

$ ollama run deepseek-r1:32b

llama.cpp

$ llama-cli -hf bartowski/DeepSeek-R1-Distill-Qwen-32B-GGUF:Q4_K_M

LM Studio

$ lms get bartowski/DeepSeek-R1-Distill-Qwen-32B-GGUF

Which devices can run DeepSeek-R1-Distill-Qwen 32B?

Apple Silicon Macs

RAM-only laptops

iPhone & iPad

Android

NVIDIA GPUs

AMD GPUs

Same job, different size

Pick by what fits your memory: step down to free up VRAM, or step up if you have headroom.

Next size down North Mini Code 1.0 30.5B Next size up Gemma 4 31B 32.7B

Similar models

Head-to-head

FAQ

How much VRAM or RAM does DeepSeek-R1-Distill-Qwen 32B need?

At Q4_K_M, DeepSeek-R1-Distill-Qwen 32B needs about 22.1 GB (weights ~19.85 GB + KV cache + overhead) at a 4k context. At Q8_0 budget ~37 GB.

What is the Q4_K_M GGUF file size of DeepSeek-R1-Distill-Qwen 32B?

The Q4_K_M GGUF file is about 19.85 GB to download, and the Q8_0 GGUF is about 34.82 GB. That is the weights file on disk; to run it you also need room for the KV cache and overhead, so budget ~22.1 GB of memory at Q4_K_M.

Can DeepSeek-R1-Distill-Qwen 32B run on a laptop?

DeepSeek-R1-Distill-Qwen 32B is large; you need a 24 GB+ GPU or a 32-48 GB Mac at Q4_K_M.

Can I use DeepSeek-R1-Distill-Qwen 32B commercially?

Yes. DeepSeek-R1-Distill-Qwen 32B is licensed MIT, which permits commercial use.

Understand the numbers

Short guides to the ideas behind DeepSeek-R1-Distill-Qwen 32B's memory and quant figures.

Distilled from DeepSeek-R1 onto Qwen2.5-32B base. Released 2025-01-20. Q4_K_M=19.85GB, Q8_0=34.82GB from bartowski HF repo. Ollama shows 20GB. Context 128K.

Sources

Last validated 2026-08-03. Memory figures are estimates. See methodology.