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 12 GB at 128k, counting the weights, the KV cache and runtime buffers. The cheapest hardware in the UK that runs DeepSeek R1 Distill Qwen 7B fully in memory at 128k context is the NVIDIA GeForce RTX 5060 Ti 16GB, £550 at eBay, at about 20 tok/s (estimated).

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

What to run it on in the UK

Fully in memory at 128k 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 Tesla P40Q8_0fits14 tok/s£26152.6
AMD Radeon RX 7600 XTQ6_Kfits12 tok/s£34833.0
AMD Radeon RX 9060 XT 16GBQ6_Kfits13 tok/s£49925.7
NVIDIA GeForce RTX 5060 Ti 16GBQ6_Kfits20 tok/s£55036.7
AMD Radeon RX 7800 XTQ6_Kfits25 tok/s£56843.8
Intel Arc A770 16GBQ6_Kfits20 tok/s£58834.5
AMD Radeon RX 9070 XTQ6_Kfits26 tok/s£67038.2
Intel Arc Pro B60Q8_0fits15 tok/s£74219.7
AMD Radeon RX 7900 XTQ8_0fits28 tok/s£78935.7
NVIDIA GeForce RTX 4070 Ti SuperQ6_Kfits30 tok/s£95031.9
NVIDIA GeForce RTX 5070 TiQ6_Kfits40 tok/s£97541.3
NVIDIA GeForce RTX 4060 Ti 16GBQ6_Kfits13 tok/s£97713.3
AMD Radeon RX 7900 XTXQ8_0fits34 tok/s£99933.8
NVIDIA GeForce RTX 5080Q6_Kfits43 tok/s£1,19936.0
Mac mini M4 32GBQ8_0fits5 tok/s£1,2004.2
NVIDIA GeForce RTX 4080 SuperQ6_Kfits33 tok/s£1,42923.2
AMD Radeon AI PRO R9700Q8_0fits23 tok/s£1,67413.4
NVIDIA GeForce RTX 3090Q8_0fits37 tok/s£1,70721.8
NVIDIA GeForce RTX 3090 TiQ8_0fits40 tok/s£2,19918.2
Mac mini M4 Pro 48GBQ8_0fits11 tok/s£3,0003.8
GMKtec EVO-X2 Ryzen AI Max+ 395 128GBQ8_0fits9 tok/s£3,3202.7
Mac Studio M4 Max 64GBQ8_0fits23 tok/s£3,3996.7
NVIDIA GeForce RTX 5090Q8_0fits71 tok/s£5,00014.2
Mac Studio M3 Ultra 96GBQ8_0fits34 tok/s£5,4996.2
NVIDIA GeForce RTX 4090Q8_0fits40 tok/s£6,0156.6
Mac Studio M3 Ultra 256GBQ8_0fits34 tok/s£8,4994.0
Mac Studio M3 Ultra 512GBQ8_0fits34 tok/s£17,4951.9
NVIDIA RTX PRO 6000 BlackwellQ8_0fits71 tok/s£29,5042.4
Mac Studio M4 Max 128GBQ8_0fits23 tok/s––
Mac mini M4 Pro 64GBQ8_0fits11 tok/s––
Framework Desktop Ryzen AI Max+ 395 128GBQ8_0fits9 tok/s––
NVIDIA DGX Spark 128GBQ8_0fits11 tok/s––
ASUS Ascent GX10 128GBQ8_0fits11 tok/s––
Framework Desktop Ryzen AI Max+ 395 64GBQ8_0fits9 tok/s––
Intel Arc B580Q4_K_Moffload13 tok/s£34936.2
NVIDIA GeForce RTX 3060 12GBQ4_K_Moffload13 tok/s£39033.6
NVIDIA GeForce RTX 3080 10GBQ4_K_Moffload12 tok/s£46624.9
NVIDIA GeForce RTX 5070Q4_K_Moffload19 tok/s£69526.8
NVIDIA GeForce RTX 4070 SuperQ4_K_Moffload16 tok/s£87418.3

1 other card or machine we price cannot hold it at this context.

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 12 GB at 128k, 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 the UK that runs DeepSeek R1 Distill Qwen 7B fully in memory at 128k context is the NVIDIA GeForce RTX 5060 Ti 16GB, £550 at eBay, at about 20 tok/s (estimated). The best value is the AMD Radeon RX 7800 XT (about 25 tok/s for £568). The fastest we price is the NVIDIA GeForce RTX 5090, at about 71 tok/s.
Can I run DeepSeek R1 Distill Qwen 7B on a 16 GB GPU?
Yes: at Q6_K it fits fully in 16 GB at 128k context. On the NVIDIA GeForce RTX 5080 it runs at about 43 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 128k context. On the NVIDIA GeForce RTX 3090 Ti it runs at about 40 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.