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Text model · DeepSeek-R1-Distill

DeepSeek-R1-Distill-Qwen 14B: RAM and VRAM requirements

DeepSeek-R1-Distill-Qwen 14B needs about 10.7 GB to run at Q4_K_M (the Q4_K_M GGUF file is ~8.99 GB to download; KV cache and overhead add the rest), or about 17.4 GB at Q8_0. The lightest hardware that runs it is Nvidia GeForce RTX 3060 (12GB).

DeepSeek-R1-Distill family · 14B params · released Jan 2025 · 79.3M Ollama pulls.

Shopping for hardware? See what runs DeepSeek-R1-Distill-Qwen 14B →

License MIT · Commercial OK ↓ 730.3K/mo ♥ 666 on HuggingFace
Q4_K_M GGUF
8.99 GB
Q8_0 GGUF
15.7 GB
Memory @ Q4 (4k)
~10.7 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 14B runs on 24 of 40 tracked devices at Q4_K_M.

22 run well 2 tight fit 16 too small
Fit check Q4_K_M
No, not enough memory
needs 10.7 GB usable 10.5 GB
See the full breakdown

Memory breakdown

Weights (Q4_K_M)8.99 GB
+
KV cache (4k)0.9 GB
+
Overhead0.8 GB
=
Total10.7 GB

How context length changes it

4k context ~10.7 GB 32k context ~17 GB 128k context ~38.5 GB

Longer context grows the KV cache quickly: DeepSeek-R1-Distill-Qwen 14B needs ~10.7 GB at 4k but ~38.5 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-Distill-Qwen 14B generates at roughly ~24% of its short-context speed. How this is estimated.

Quantization sizes

GGUF quantson disk
Quantization Size on disk
Q2_K 5.9 GB est
Q3_K_M 6.8 GB est
Q4_K_M (default) 8.99 GB
Q5_K_M 10 GB est
Q6_K 11.5 GB est
Q8_0 15.7 GB
FP16 28 GB est

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

Run it

Ollama
$ ollama run deepseek-r1:14b
llama.cpp
$ llama-cli -hf bartowski/DeepSeek-R1-Distill-Qwen-14B-GGUF:Q4_K_M
LM Studio
$ lms get bartowski/DeepSeek-R1-Distill-Qwen-14B-GGUF

Which devices can run DeepSeek-R1-Distill-Qwen 14B?

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 Mistral Nemo 12B 12.2B Next size up DeepSeek-V2-Lite 16B

Similar models

Head-to-head

FAQ

How much VRAM or RAM does DeepSeek-R1-Distill-Qwen 14B need?

At Q4_K_M, DeepSeek-R1-Distill-Qwen 14B needs about 10.7 GB (weights ~8.99 GB + KV cache + overhead) at a 4k context. At Q8_0 budget ~17.4 GB.

What is the Q4_K_M GGUF file size of DeepSeek-R1-Distill-Qwen 14B?

The Q4_K_M GGUF file is about 8.99 GB to download, and the Q8_0 GGUF is about 15.7 GB. That is the weights file on disk; to run it you also need room for the KV cache and overhead, so budget ~10.7 GB of memory at Q4_K_M.

Can DeepSeek-R1-Distill-Qwen 14B run on a laptop?

DeepSeek-R1-Distill-Qwen 14B 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 14B commercially?

Yes. DeepSeek-R1-Distill-Qwen 14B is licensed MIT, which permits commercial use.

Understand the numbers

Short guides to the ideas behind DeepSeek-R1-Distill-Qwen 14B's memory and quant figures.

Distilled from DeepSeek-R1 onto Qwen2.5-14B base. Released 2025-01-20. Q4_K_M=8.99GB, Q8_0=15.70GB from bartowski HF repo. Ollama shows 9.0GB. Context 128K.

Sources

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