DeepSeek R1 Distill Qwen 7B

7.6B parameters · 128k context · MIT License · released 2025-01-20

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In short

DeepSeek R1 Distill Qwen 7B is an open model from DeepSeek with 7.6B parameters. At mlx-3bit, DeepSeek R1 Distill Qwen 7B needs about 4 GB of memory at 8k context and 6 GB at 32k, counting the weights, the KV cache and runtime buffers. The cheapest hardware in Canada that runs DeepSeek R1 Distill Qwen 7B fully in memory at 32k context is the NVIDIA GeForce RTX 3060 12GB, $497 at Amazon, at about 22 tok/s (estimated).

Updated . Speeds are estimates; how they are worked out.

What to run it on in Canada

Fully in memory at 32k context, priced at retailers today.

All hardware that runs it

Everything we price, best value first. Two cards split the model by layers.

HardwareQuantFitsDecodePricetok/s per 1,000
NVIDIA GeForce RTX 3060 12GBQ8_0fits22 tok/s$49745.1
Intel Arc B580Q8_0fits23 tok/s$56040.9
Intel Arc A770 16GBQ8_0fits28 tok/s$65542.9
NVIDIA GeForce RTX 3080 10GBQ6_Kfits58 tok/s$76975.3
AMD Radeon RX 9060 XT 16GBQ8_0fits18 tok/s$80022.0
AMD Radeon RX 9070 XTQ8_0fits35 tok/s$1,05033.6
Intel Arc Pro B60Q8_0fits23 tok/s$1,06021.6
NVIDIA GeForce RTX 5060 Ti 16GBQ8_0fits28 tok/s$1,12024.8
NVIDIA GeForce RTX 5070Q8_0fits42 tok/s$1,18135.4
AMD Radeon RX 7800 XTQ8_0fits34 tok/s$1,39724.6
Mac mini M4 16GBQ8_0fits8 tok/s$1,3995.6
NVIDIA GeForce RTX 4070 SuperQ8_0fits31 tok/s$1,40022.4
AMD Radeon RX 7600 XTQ8_0fits16 tok/s$1,44011.0
NVIDIA GeForce RTX 5070 TiQ8_0fits56 tok/s$1,69033.0
NVIDIA GeForce RTX 4070 Ti SuperQ8_0fits42 tok/s$1,79023.4
NVIDIA GeForce RTX 4080 SuperQ8_0fits46 tok/s$2,00022.9
AMD Radeon RX 7900 XTQ8_0fits44 tok/s$2,08321.2
NVIDIA GeForce RTX 5080Q8_0fits60 tok/s$2,37025.2
NVIDIA GeForce RTX 3090Q8_0fits58 tok/s$2,80020.8
AMD Radeon AI PRO R9700Q8_0fits35 tok/s$2,80012.6
NVIDIA RTX PRO 6000 BlackwellQ8_0fits111 tok/s$3,13335.6
NVIDIA GeForce RTX 3090 TiQ8_0fits63 tok/s$3,99915.7
GMKtec EVO-X2 Ryzen AI Max+ 395 128GBQ8_0fits14 tok/s$5,0992.8
NVIDIA GeForce RTX 4090Q8_0fits63 tok/s$7,1078.8
ASUS Ascent GX10 128GBQ8_0fits17 tok/s$8,2992.0
NVIDIA GeForce RTX 5090Q8_0fits111 tok/s$10,30010.8
Mac Studio M4 Max 128GBQ8_0fits36 tok/s––
Mac mini M4 Pro 64GBQ8_0fits18 tok/s––
AMD Radeon RX 7900 XTXQ8_0fits53 tok/s––
Framework Desktop Ryzen AI Max+ 395 128GBQ8_0fits14 tok/s––
Mac Studio M3 Ultra 512GBQ8_0fits53 tok/s––
NVIDIA DGX Spark 128GBQ8_0fits17 tok/s––
Mac Studio M3 Ultra 256GBQ8_0fits53 tok/s––
Mac mini M4 Pro 48GBQ8_0fits18 tok/s––
NVIDIA GeForce RTX 4060 Ti 16GBQ8_0fits18 tok/s––
Mac Studio M4 Max 64GBQ8_0fits36 tok/s––
Mac Studio M3 Ultra 96GBQ8_0fits53 tok/s––
Framework Desktop Ryzen AI Max+ 395 64GBQ8_0fits14 tok/s––
Mac mini M4 32GBQ8_0fits8 tok/s––
NVIDIA Tesla P40Q8_0fits22 tok/s––

Memory needed

Weights, KV cache and runtime buffers at each context length (KV cache at fp16).

QuantFile@8k@32k@64k@128k
mlx-3bitmlx3.1 GB4.3 GB5.7 GB7.7 GB11.6 GB
mlx-4bitmlx4.0 GB5.2 GB6.6 GB8.6 GB12.4 GB
Q4_K_Mgguf4.4 GB5.5 GB7.0 GB8.9 GB12.8 GB
Q5_K_Mgguf5.1 GB6.3 GB7.7 GB9.6 GB13.5 GB
mlx-6bitmlx5.8 GB6.9 GB8.4 GB10.3 GB14.2 GB
Q6_Kgguf5.8 GB7.0 GB8.5 GB10.4 GB14.3 GB
mlx-8bitmlx7.5 GB8.7 GB10.2 GB12.1 GB16.0 GB
Q8_0gguf7.5 GB8.7 GB10.2 GB12.1 GB16.0 GB

Run it

Copy a command for the runtime you use.

  • mlx-3bit
    • LM Studiolms get mlx-community/DeepSeek-R1-Distill-Qwen-7B-3bit
    • MLXmlx_lm.server --model mlx-community/DeepSeek-R1-Distill-Qwen-7B-3bit
  • mlx-4bit
    • LM Studiolms get mlx-community/DeepSeek-R1-Distill-Qwen-7B-4bit
    • MLXmlx_lm.server --model mlx-community/DeepSeek-R1-Distill-Qwen-7B-4bit
  • Q4_K_M
    • Ollamaollama run hf.co/unsloth/DeepSeek-R1-Distill-Qwen-7B-GGUF:Q4_K_M
    • LM Studiolms get unsloth/DeepSeek-R1-Distill-Qwen-7B-GGUF@q4_k_m
    • llama.cppllama-server -hf unsloth/DeepSeek-R1-Distill-Qwen-7B-GGUF:Q4_K_M
  • Q5_K_M
    • Ollamaollama run hf.co/unsloth/DeepSeek-R1-Distill-Qwen-7B-GGUF:Q5_K_M
    • LM Studiolms get unsloth/DeepSeek-R1-Distill-Qwen-7B-GGUF@q5_k_m
    • llama.cppllama-server -hf unsloth/DeepSeek-R1-Distill-Qwen-7B-GGUF:Q5_K_M
  • mlx-6bit
    • LM Studiolms get mlx-community/DeepSeek-R1-Distill-Qwen-7B-6bit
    • MLXmlx_lm.server --model mlx-community/DeepSeek-R1-Distill-Qwen-7B-6bit
  • Q6_K
    • Ollamaollama run hf.co/unsloth/DeepSeek-R1-Distill-Qwen-7B-GGUF:Q6_K
    • LM Studiolms get unsloth/DeepSeek-R1-Distill-Qwen-7B-GGUF@q6_k
    • llama.cppllama-server -hf unsloth/DeepSeek-R1-Distill-Qwen-7B-GGUF:Q6_K
  • mlx-8bit
    • LM Studiolms get mlx-community/DeepSeek-R1-Distill-Qwen-7B-8bit
    • MLXmlx_lm.server --model mlx-community/DeepSeek-R1-Distill-Qwen-7B-8bit
  • Q8_0
    • Ollamaollama run hf.co/unsloth/DeepSeek-R1-Distill-Qwen-7B-GGUF:Q8_0
    • LM Studiolms get unsloth/DeepSeek-R1-Distill-Qwen-7B-GGUF@q8_0
    • llama.cppllama-server -hf unsloth/DeepSeek-R1-Distill-Qwen-7B-GGUF:Q8_0

Notes

Distilled from DeepSeek-R1 onto Qwen2.5-Math-7B (Qwen2.5 series is Apache 2.0); the card licenses the weights under MIT. Use temperature 0.5-0.7, no system prompt, and start output with "<think>\n".

Questions

How much VRAM does DeepSeek R1 Distill Qwen 7B need?
At mlx-3bit, DeepSeek R1 Distill Qwen 7B needs about 4 GB of memory at 8k context and 6 GB at 32k, counting the weights, the KV cache and runtime buffers.
What is the best GPU for running DeepSeek R1 Distill Qwen 7B locally?
The cheapest hardware in Canada that runs DeepSeek R1 Distill Qwen 7B fully in memory at 32k context is the NVIDIA GeForce RTX 3060 12GB, $497 at Amazon, at about 22 tok/s (estimated). The best value is the NVIDIA GeForce RTX 3080 10GB (about 58 tok/s for $769). The fastest we price is the NVIDIA RTX PRO 6000 Blackwell, at about 111 tok/s.
Can I run DeepSeek R1 Distill Qwen 7B on a 16 GB GPU?
Yes: at Q8_0 it fits fully in 16 GB at 32k context. On the NVIDIA GeForce RTX 5080 it runs at about 60 tok/s (estimated).
Can I run DeepSeek R1 Distill Qwen 7B on a 24 GB GPU?
Yes: at Q8_0 it fits fully in 24 GB at 32k context. On the NVIDIA GeForce RTX 3090 Ti it runs at about 63 tok/s (estimated).
How do I run DeepSeek R1 Distill Qwen 7B locally?
With Ollama: ollama run hf.co/unsloth/DeepSeek-R1-Distill-Qwen-7B-GGUF:Q4_K_M (the Q4_K_M build). LM Studio and llama.cpp commands are on this page.
What licence is DeepSeek R1 Distill Qwen 7B released under?
MIT License, which allows commercial use.