readygpu

Qwen 3.8 27B

27.8B parameters · 256k context · apache-2.0 · released 2026-08-05

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What to run it on in the US

Fully in memory at 8k 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
Intel Arc Pro B60UD-Q6_Kfits10 tok/s$65015.5
AMD Radeon RX 7900 XTUD-Q4_K_Mfits26 tok/s$80032.1
AMD Radeon RX 7900 XTXUD-Q6_Kfits23 tok/s$1,53315.2
NVIDIA GeForce RTX 3090UD-Q6_Kfits26 tok/s$1,66015.4
AMD Radeon AI PRO R9700Q8_0fits12 tok/s$1,7006.9
NVIDIA GeForce RTX 3090 TiUD-Q6_Kfits28 tok/s$2,06013.4
NVIDIA GeForce RTX 4090UD-Q6_Kfits28 tok/s$3,2808.4
NVIDIA GeForce RTX 5090Q8_0fits37 tok/s$7,2005.2
Mac Studio M4 Max 128GBQ8_0fits12 tok/s––
Mac mini M4 Pro 64GBQ8_0fits6 tok/s––
Framework Desktop Ryzen AI Max+ 395 128GBQ8_0fits5 tok/s––
Mac Studio M3 Ultra 512GBQ8_0fits18 tok/s––
NVIDIA DGX Spark 128GBQ8_0fits6 tok/s––
GMKtec EVO-X2 Ryzen AI Max+ 395 128GBQ8_0fits5 tok/s––
Mac Studio M3 Ultra 256GBQ8_0fits18 tok/s––
Mac mini M4 Pro 48GBQ8_0fits6 tok/s––
Mac Studio M4 Max 64GBQ8_0fits12 tok/s––
Mac Studio M3 Ultra 96GBQ8_0fits18 tok/s––
NVIDIA RTX PRO 6000 BlackwellQ8_0fits37 tok/s––
ASUS Ascent GX10 128GBQ8_0fits6 tok/s––
Framework Desktop Ryzen AI Max+ 395 64GBQ8_0fits5 tok/s––
Mac mini M4 32GBUD-Q5_K_Mfits4 tok/s––
NVIDIA Tesla P40UD-Q6_Kfits10 tok/s––
NVIDIA GeForce RTX 3060 12GBUD-Q4_K_Moffload6 tok/s$36017.5
Intel Arc B580UD-Q4_K_Moffload6 tok/s$37016.8
Intel Arc A770 16GBUD-Q4_K_Moffload11 tok/s$40028.5
NVIDIA GeForce RTX 3080 10GBUD-Q4_K_Moffload6 tok/s$46912.8
AMD Radeon RX 9060 XT 16GBUD-Q4_K_Moffload8 tok/s$54315.3
AMD Radeon RX 7800 XTUD-Q4_K_Moffload13 tok/s$59921.5
AMD Radeon RX 7600 XTUD-Q4_K_Moffload8 tok/s$69511.1
NVIDIA GeForce RTX 4070 SuperUD-Q4_K_Moffload7 tok/s$69910.0
NVIDIA GeForce RTX 4060 Ti 16GBUD-Q4_K_Moffload9 tok/s$77011.3
NVIDIA GeForce RTX 5060 Ti 16GBUD-Q4_K_Moffload12 tok/s$77215.5
NVIDIA GeForce RTX 5070UD-Q4_K_Moffload8 tok/s$7769.7
AMD Radeon RX 9070 XTUD-Q4_K_Moffload13 tok/s$81516.1
NVIDIA GeForce RTX 4070 Ti SuperUD-Q4_K_Moffload16 tok/s$1,01315.4
NVIDIA GeForce RTX 5070 TiUD-Q4_K_Moffload18 tok/s$1,14416.0
NVIDIA GeForce RTX 4080 SuperUD-Q4_K_Moffload16 tok/s$1,19913.7
NVIDIA GeForce RTX 5080UD-Q4_K_Moffload19 tok/s$1,73810.9

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
UD-Q4_K_Mgguf15.3 GB16.7 GB18.4 GB20.5 GB24.9 GB
mlx-4bitmlx15.0 GB16.3 GB18.0 GB20.2 GB24.5 GB
UD-Q5_K_Mgguf18.4 GB19.8 GB21.4 GB23.6 GB28.0 GB
UD-Q6_Kgguf20.5 GB21.9 GB23.5 GB25.7 GB30.1 GB
Q8_0gguf27.1 GB28.4 GB30.1 GB32.3 GB36.6 GB
mlx-8bitmlx27.5 GB28.9 GB30.5 GB32.7 GB37.1 GB

Run it

Copy a command for the runtime you use.

  • UD-Q4_K_M
    • Ollamaollama run hf.co/unsloth/Qwen3.8-27B-GGUF:UD-Q4_K_M
    • LM Studiolms get unsloth/Qwen3.8-27B-GGUF@ud-q4_k_m
    • llama.cppllama-server -hf unsloth/Qwen3.8-27B-GGUF:UD-Q4_K_M
  • mlx-4bit
    • LM Studiolms get mlx-community/Qwen3.8-27B-4bit
    • MLXmlx_lm.server --model mlx-community/Qwen3.8-27B-4bit
  • UD-Q5_K_M
    • Ollamaollama run hf.co/unsloth/Qwen3.8-27B-GGUF:UD-Q5_K_M
    • LM Studiolms get unsloth/Qwen3.8-27B-GGUF@ud-q5_k_m
    • llama.cppllama-server -hf unsloth/Qwen3.8-27B-GGUF:UD-Q5_K_M
  • UD-Q6_K
    • Ollamaollama run hf.co/unsloth/Qwen3.8-27B-GGUF:UD-Q6_K
    • LM Studiolms get unsloth/Qwen3.8-27B-GGUF@ud-q6_k
    • llama.cppllama-server -hf unsloth/Qwen3.8-27B-GGUF:UD-Q6_K
  • Q8_0
    • Ollamaollama run hf.co/unsloth/Qwen3.8-27B-GGUF:Q8_0
    • LM Studiolms get unsloth/Qwen3.8-27B-GGUF@q8_0
    • llama.cppllama-server -hf unsloth/Qwen3.8-27B-GGUF:Q8_0
  • mlx-8bit
    • LM Studiolms get mlx-community/Qwen3.8-27B-8bit
    • MLXmlx_lm.server --model mlx-community/Qwen3.8-27B-8bit