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Text model · DeepSeek-R1-Distill

DeepSeek-R1-Distill-Llama 8B requirements

DeepSeek-R1-Distill family · 8B params · released Jan 2025 · 79.3M Ollama pulls. Minimum to run at Q4_K_M: Nvidia GeForce RTX 3060 (12GB).

LicenseMIT· Commercial OK↓ 381.2K/mo♥ 865on HuggingFace
Q4_K_M
4.92 GB
Q8_0
8.54 GB
Total @ Q4 (4k)
~6.4 GB
Context
128 k

Quantization sizes

GGUF quantson disk
QuantizationSize on disk
Q2_K3.4 GB est
Q3_K_M3.9 GB est
Q4_K_M (default)4.92 GB
Q5_K_M5.7 GB est
Q6_K6.6 GB est
Q8_08.54 GB
FP1616 GB est

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

Run it

Ollama
$ ollama run deepseek-r1:8b
llama.cpp
$ llama-cli -hf bartowski/DeepSeek-R1-Distill-Llama-8B-GGUF:Q4_K_M
LM Studio
$ lms get bartowski/DeepSeek-R1-Distill-Llama-8B-GGUF

Which devices can run DeepSeek-R1-Distill-Llama 8B?

FAQ

How much VRAM or RAM does DeepSeek-R1-Distill-Llama 8B need?

At Q4_K_M, DeepSeek-R1-Distill-Llama 8B needs about 6.4 GB (weights ~4.92 GB + KV cache + overhead) at a 4k context. At Q8_0 budget ~10 GB.

Can DeepSeek-R1-Distill-Llama 8B run on a laptop?

Yes, DeepSeek-R1-Distill-Llama 8B fits on a 16 GB machine at Q4_K_M and runs on Apple Silicon or a 12 GB+ GPU comfortably.

Can I use DeepSeek-R1-Distill-Llama 8B commercially?

Yes. DeepSeek-R1-Distill-Llama 8B is licensed MIT, which permits commercial use.

Distilled from DeepSeek-R1 onto Llama-3.1-8B base. Released 2025-01-20. Q4_K_M=4.92GB, Q8_0=8.54GB from bartowski HF repo. Ollama shows 5.2GB for the 8b tag. Context 128K.

Sources

Memory figures are estimates. See methodology.