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Text model · DeepSeek-R1-Distill

DeepSeek-R1-0528-Qwen3-8B: RAM and VRAM requirements

DeepSeek-R1-0528-Qwen3-8B needs about 6.2 GB to run at Q4_K_M (the Q4_K_M GGUF file is ~4.68 GB to download; KV cache and overhead add the rest), or about 9.6 GB at Q8_0. The lightest hardware that runs it is Nvidia GeForce RTX 3060 (12GB).

DeepSeek-R1-Distill family · 8.19B params · released May 2025.

Shopping for hardware? See what runs DeepSeek-R1-0528-Qwen3-8B →

License MIT · Commercial OK ↓ 1.7M/mo ♥ 1.1K on HuggingFace
Q4_K_M GGUF
4.68 GB
Q8_0 GGUF
8.11 GB
Memory @ Q4 (4k)
~6.2 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-R1-0528-Qwen3-8B runs on 33 of 40 tracked devices at Q4_K_M.

33 run well 0 tight fit 7 too small
Fit check Q4_K_M
Yes, it runs fast
needs 6.2 GB usable 10.5 GB
See the full breakdown
$ollama run deepseek-r1:8b-0528-qwen3-q4_K_M

Memory breakdown

Weights (Q4_K_M)4.68 GB
+
KV cache (4k)0.7 GB
+
Overhead0.8 GB
=
Total6.2 GB

How context length changes it

4k context ~6.2 GB 32k context ~11 GB 128k context ~27.5 GB

Longer context grows the KV cache quickly: DeepSeek-R1-0528-Qwen3-8B needs ~6.2 GB at 4k but ~27.5 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-R1-0528-Qwen3-8B generates at roughly ~18% of its short-context speed. How this is estimated.

Quantization sizes

GGUF quantson disk
Quantization Size on disk
Q2_K 3.4 GB est
Q3_K_M 4 GB est
Q4_K_M (default) 4.68 GB
Q5_K_M 5.8 GB est
Q6_K 6.7 GB est
Q8_0 8.11 GB
FP16 16.4 GB

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

Run it

Ollama
$ ollama run deepseek-r1:8b-0528-qwen3-q4_K_M
llama.cpp
$ llama-cli -hf unsloth/DeepSeek-R1-0528-Qwen3-8B-GGUF:Q4_K_M
LM Studio
$ lms get unsloth/DeepSeek-R1-0528-Qwen3-8B-GGUF

Which devices can run DeepSeek-R1-0528-Qwen3-8B?

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 Gemma 4 E4B 8B Next size up Qwen2.5-VL 7B 8.29B

Similar models

Head-to-head

FAQ

How much VRAM or RAM does DeepSeek-R1-0528-Qwen3-8B need?

At Q4_K_M, DeepSeek-R1-0528-Qwen3-8B needs about 6.2 GB (weights ~4.68 GB + KV cache + overhead) at a 4k context. At Q8_0 budget ~9.6 GB.

What is the Q4_K_M GGUF file size of DeepSeek-R1-0528-Qwen3-8B?

The Q4_K_M GGUF file is about 4.68 GB to download, and the Q8_0 GGUF is about 8.11 GB. That is the weights file on disk; to run it you also need room for the KV cache and overhead, so budget ~6.2 GB of memory at Q4_K_M.

Can DeepSeek-R1-0528-Qwen3-8B run on a laptop?

DeepSeek-R1-0528-Qwen3-8B is large; you need a 24 GB+ GPU or a 32-48 GB Mac at Q4_K_M.

Can I use DeepSeek-R1-0528-Qwen3-8B commercially?

Yes. DeepSeek-R1-0528-Qwen3-8B is licensed MIT, which permits commercial use.

Understand the numbers

Short guides to the ideas behind DeepSeek-R1-0528-Qwen3-8B's memory and quant figures.

The runnable distill of R1-0528 into Qwen3-8B. Brings the updated reasoning to a 16GB machine.

Sources

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