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DeepSeek R1 Distill Qwen 14B

14.8B parameters · 128k context · MIT License · released 2025-01-20

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In short

DeepSeek R1 Distill Qwen 14B is an open model from DeepSeek with 14.8B parameters. At mlx-3bit, DeepSeek R1 Distill Qwen 14B needs about 8 GB of memory at 8k context and 31 GB at 128k, counting the weights, the KV cache and runtime buffers. The cheapest hardware in the UK that runs DeepSeek R1 Distill Qwen 14B fully in memory at 128k context is the NVIDIA RTX PRO 6000 Blackwell, £29,504 at Amazon, at about 27 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
Mac mini M4 Pro 48GBQ5_K_Mfits5 tok/s£3,0001.6
GMKtec EVO-X2 Ryzen AI Max+ 395 128GBQ8_0fits3 tok/s£3,3201.0
Mac Studio M4 Max 64GBQ8_0fits9 tok/s£3,3992.5
Mac Studio M3 Ultra 96GBQ8_0fits13 tok/s£5,4992.3
Mac Studio M3 Ultra 256GBQ8_0fits13 tok/s£8,4991.5
Mac Studio M3 Ultra 512GBQ8_0fits13 tok/s£17,4950.7
NVIDIA RTX PRO 6000 BlackwellQ8_0fits27 tok/s£29,5040.9
Mac Studio M4 Max 128GBQ8_0fits9 tok/s––
Mac mini M4 Pro 64GBQ8_0fits4 tok/s––
Framework Desktop Ryzen AI Max+ 395 128GBQ8_0fits3 tok/s––
NVIDIA DGX Spark 128GBQ8_0fits4 tok/s––
ASUS Ascent GX10 128GBQ8_0fits4 tok/s––
Framework Desktop Ryzen AI Max+ 395 64GBQ8_0fits3 tok/s––
NVIDIA Tesla P40Q4_K_Moffload3 tok/s£26111.9
AMD Radeon RX 7600 XTQ4_K_Moffload2 tok/s£3486.0
Intel Arc B580Q4_K_Moffload2 tok/s£3495.7
NVIDIA GeForce RTX 3060 12GBQ4_K_Moffload2 tok/s£3905.1
NVIDIA GeForce RTX 3080 10GBQ4_K_Moffload2 tok/s£4664.3
AMD Radeon RX 9060 XT 16GBQ4_K_Moffload2 tok/s£4994.4
NVIDIA GeForce RTX 5060 Ti 16GBQ4_K_Moffload2 tok/s£5504.4
AMD Radeon RX 7800 XTQ4_K_Moffload2 tok/s£5684.2
Intel Arc A770 16GBQ4_K_Moffload2 tok/s£5883.9
AMD Radeon RX 9070 XTQ4_K_Moffload2 tok/s£6703.6
NVIDIA GeForce RTX 5070Q4_K_Moffload2 tok/s£6953.0
Intel Arc Pro B60Q4_K_Moffload3 tok/s£7424.3
AMD Radeon RX 7900 XTQ4_K_Moffload3 tok/s£7893.8
NVIDIA GeForce RTX 4070 SuperQ4_K_Moffload2 tok/s£8742.4
NVIDIA GeForce RTX 4070 Ti SuperQ4_K_Moffload3 tok/s£9502.6
NVIDIA GeForce RTX 5070 TiQ4_K_Moffload3 tok/s£9752.6
NVIDIA GeForce RTX 4060 Ti 16GBQ4_K_Moffload2 tok/s£9772.3
AMD Radeon RX 7900 XTXQ4_K_Moffload4 tok/s£9993.9
NVIDIA GeForce RTX 5080Q4_K_Moffload3 tok/s£1,1992.1
NVIDIA GeForce RTX 4080 SuperQ4_K_Moffload3 tok/s£1,4291.7
AMD Radeon AI PRO R9700Q4_K_Moffload7 tok/s£1,6744.1
NVIDIA GeForce RTX 3090Q4_K_Moffload4 tok/s£1,7072.3
NVIDIA GeForce RTX 3090 TiQ4_K_Moffload4 tok/s£2,1991.9
NVIDIA GeForce RTX 5090Q4_K_Moffload13 tok/s£5,0002.6
NVIDIA GeForce RTX 4090Q4_K_Moffload4 tok/s£6,0150.7

2 other cards and machines 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-3bitmlx6.0 GB8.3 GB12.9 GB19.1 GB31.5 GB
mlx-4bitmlx7.7 GB10.0 GB14.6 GB20.8 GB33.2 GB
Q4_K_Mgguf8.4 GB10.6 GB15.3 GB21.4 GB33.8 GB
Q5_K_Mgguf9.8 GB12.0 GB16.7 GB22.9 GB35.2 GB
mlx-6bitmlx11.2 GB13.4 GB18.1 GB24.3 GB36.6 GB
Q6_Kgguf11.3 GB13.5 GB18.2 GB24.4 GB36.7 GB
mlx-8bitmlx14.6 GB16.9 GB21.5 GB27.7 GB40.1 GB
Q8_0gguf14.6 GB16.9 GB21.5 GB27.7 GB40.1 GB

Run it

Copy a command for the runtime you use.

  • mlx-3bit
    • LM Studiolms get mlx-community/DeepSeek-R1-Distill-Qwen-14B-3bit
    • MLXmlx_lm.server --model mlx-community/DeepSeek-R1-Distill-Qwen-14B-3bit
  • mlx-4bit
    • LM Studiolms get mlx-community/DeepSeek-R1-Distill-Qwen-14B-4bit
    • MLXmlx_lm.server --model mlx-community/DeepSeek-R1-Distill-Qwen-14B-4bit
  • Q4_K_M
    • Ollamaollama run hf.co/unsloth/DeepSeek-R1-Distill-Qwen-14B-GGUF:Q4_K_M
    • LM Studiolms get unsloth/DeepSeek-R1-Distill-Qwen-14B-GGUF@q4_k_m
    • llama.cppllama-server -hf unsloth/DeepSeek-R1-Distill-Qwen-14B-GGUF:Q4_K_M
  • Q5_K_M
    • Ollamaollama run hf.co/unsloth/DeepSeek-R1-Distill-Qwen-14B-GGUF:Q5_K_M
    • LM Studiolms get unsloth/DeepSeek-R1-Distill-Qwen-14B-GGUF@q5_k_m
    • llama.cppllama-server -hf unsloth/DeepSeek-R1-Distill-Qwen-14B-GGUF:Q5_K_M
  • mlx-6bit
    • LM Studiolms get mlx-community/DeepSeek-R1-Distill-Qwen-14B-6bit
    • MLXmlx_lm.server --model mlx-community/DeepSeek-R1-Distill-Qwen-14B-6bit
  • Q6_K
    • Ollamaollama run hf.co/unsloth/DeepSeek-R1-Distill-Qwen-14B-GGUF:Q6_K
    • LM Studiolms get unsloth/DeepSeek-R1-Distill-Qwen-14B-GGUF@q6_k
    • llama.cppllama-server -hf unsloth/DeepSeek-R1-Distill-Qwen-14B-GGUF:Q6_K
  • mlx-8bit
    • LM Studiolms get mlx-community/DeepSeek-R1-Distill-Qwen-14B-8bit
    • MLXmlx_lm.server --model mlx-community/DeepSeek-R1-Distill-Qwen-14B-8bit
  • Q8_0
    • Ollamaollama run hf.co/unsloth/DeepSeek-R1-Distill-Qwen-14B-GGUF:Q8_0
    • LM Studiolms get unsloth/DeepSeek-R1-Distill-Qwen-14B-GGUF@q8_0
    • llama.cppllama-server -hf unsloth/DeepSeek-R1-Distill-Qwen-14B-GGUF:Q8_0

Notes

Distilled from DeepSeek-R1 onto Qwen2.5-14B (originally Apache 2.0); card says to avoid system prompts and use temperature 0.6. Card recommends forcing output to start with "<think>\n".

Questions

How much VRAM does DeepSeek R1 Distill Qwen 14B need?
At mlx-3bit, DeepSeek R1 Distill Qwen 14B needs about 8 GB of memory at 8k context and 31 GB at 128k, counting the weights, the KV cache and runtime buffers.
What is the best GPU for running DeepSeek R1 Distill Qwen 14B locally?
The cheapest hardware in the UK that runs DeepSeek R1 Distill Qwen 14B fully in memory at 128k context is the NVIDIA RTX PRO 6000 Blackwell, £29,504 at Amazon, at about 27 tok/s (estimated).
Can I run DeepSeek R1 Distill Qwen 14B on a 16 GB GPU?
Only partly: at 128k context it does not fit in 16 GB, so part of it runs from system RAM and it slows to about 2 tok/s on the AMD Radeon RX 7600 XT (estimated).
Can I run DeepSeek R1 Distill Qwen 14B on a 24 GB GPU?
Only partly: at 128k context it does not fit in 24 GB, so part of it runs from system RAM and it slows to about 3 tok/s on the NVIDIA Tesla P40 (estimated).
How do I run DeepSeek R1 Distill Qwen 14B locally?
With Ollama: ollama run hf.co/unsloth/DeepSeek-R1-Distill-Qwen-14B-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 14B released under?
MIT License, which allows commercial use.