readygpu

Qwen 3.5 122B-A10B

125.1B total, 10B active · 256k context · apache-2.0 · released 2026-02-24

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What to run it on in the UK

Fully in memory at 64k context, priced at retailers today.

Something we price holds it fully in memory, but none reaches 15 tok/s, our bar for recommending it. The table below has the speeds.

All hardware that runs it

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

HardwareQuantFitsDecodePricetok/s per 1,000
Mac Studio M4 Max 128GBQ5_K_Mfits24 tok/s––
Mac mini M4 Pro 64GBUD-Q2_K_XLfits21 tok/s––
Framework Desktop Ryzen AI Max+ 395 128GBQ5_K_Mfits9 tok/s––
Mac Studio M3 Ultra 512GBQ8_0fits26 tok/s––
NVIDIA DGX Spark 128GBQ6_Kfits10 tok/s––
GMKtec EVO-X2 Ryzen AI Max+ 395 128GBQ5_K_Mfits9 tok/s––
Mac Studio M3 Ultra 256GBQ8_0fits26 tok/s––
Mac Studio M4 Max 64GBUD-Q2_K_XLfits42 tok/s––
Mac Studio M3 Ultra 96GBQ3_K_Mfits51 tok/s––
NVIDIA RTX PRO 6000 BlackwellQ5_K_Mfits73 tok/s––
ASUS Ascent GX10 128GBQ6_Kfits10 tok/s––
Framework Desktop Ryzen AI Max+ 395 64GBUD-Q2_K_XLfits17 tok/s––
NVIDIA GeForce RTX 3090UD-Q2_K_XLoffload13 tok/s––
NVIDIA GeForce RTX 5090UD-Q2_K_XLoffload22 tok/s––
NVIDIA GeForce RTX 4090UD-Q2_K_XLoffload13 tok/s––
AMD Radeon RX 7900 XTXUD-Q2_K_XLoffload12 tok/s––
AMD Radeon AI PRO R9700UD-Q2_K_XLoffload17 tok/s––
AMD Radeon RX 7900 XTUD-Q2_K_XLoffload10 tok/s––
NVIDIA GeForce RTX 3090 TiUD-Q2_K_XLoffload13 tok/s––
Intel Arc Pro B60UD-Q2_K_XLoffload10 tok/s––
NVIDIA Tesla P40UD-Q2_K_XLoffload11 tok/s––

19 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
Q4_K_Mgguf71.3 GB72.4 GB73.1 GB74.0 GB75.9 GB
UD-Q2_K_XLgguf39.0 GB40.0 GB40.7 GB41.7 GB43.6 GB
Q3_K_Mgguf52.5 GB53.6 GB54.3 GB55.3 GB57.1 GB
mlx-4bitmlx64.8 GB65.9 GB66.6 GB67.5 GB69.4 GB
Q5_K_Mgguf85.2 GB86.3 GB87.0 GB87.9 GB89.8 GB
Q6_Kgguf94.1 GB95.1 GB95.9 GB96.8 GB98.7 GB
Q8_0gguf121.0 GB122.0 GB122.7 GB123.7 GB125.5 GB
mlx-8bitmlx121.7 GB122.8 GB123.5 GB124.4 GB126.3 GB

Run it

Copy a command for the runtime you use.

  • Q4_K_M
    • Ollamaollama run hf.co/unsloth/Qwen3.5-122B-A10B-GGUF:Q4_K_M
    • LM Studiolms get unsloth/Qwen3.5-122B-A10B-GGUF@q4_k_m
    • llama.cppllama-server -hf unsloth/Qwen3.5-122B-A10B-GGUF:Q4_K_M
  • UD-Q2_K_XL
    • Ollamaollama run hf.co/unsloth/Qwen3.5-122B-A10B-GGUF:UD-Q2_K_XL
    • LM Studiolms get unsloth/Qwen3.5-122B-A10B-GGUF@ud-q2_k_xl
    • llama.cppllama-server -hf unsloth/Qwen3.5-122B-A10B-GGUF:UD-Q2_K_XL
  • Q3_K_M
    • Ollamaollama run hf.co/unsloth/Qwen3.5-122B-A10B-GGUF:Q3_K_M
    • LM Studiolms get unsloth/Qwen3.5-122B-A10B-GGUF@q3_k_m
    • llama.cppllama-server -hf unsloth/Qwen3.5-122B-A10B-GGUF:Q3_K_M
  • mlx-4bit
    • LM Studiolms get mlx-community/Qwen3.5-122B-A10B-4bit
    • MLXmlx_lm.server --model mlx-community/Qwen3.5-122B-A10B-4bit
  • Q5_K_M
    • Ollamaollama run hf.co/unsloth/Qwen3.5-122B-A10B-GGUF:Q5_K_M
    • LM Studiolms get unsloth/Qwen3.5-122B-A10B-GGUF@q5_k_m
    • llama.cppllama-server -hf unsloth/Qwen3.5-122B-A10B-GGUF:Q5_K_M
  • Q6_K
    • Ollamaollama run hf.co/unsloth/Qwen3.5-122B-A10B-GGUF:Q6_K
    • LM Studiolms get unsloth/Qwen3.5-122B-A10B-GGUF@q6_k
    • llama.cppllama-server -hf unsloth/Qwen3.5-122B-A10B-GGUF:Q6_K
  • Q8_0
    • Ollamaollama run hf.co/unsloth/Qwen3.5-122B-A10B-GGUF:Q8_0
    • LM Studiolms get unsloth/Qwen3.5-122B-A10B-GGUF@q8_0
    • llama.cppllama-server -hf unsloth/Qwen3.5-122B-A10B-GGUF:Q8_0
  • mlx-8bit
    • LM Studiolms get mlx-community/Qwen3.5-122B-A10B-8bit
    • MLXmlx_lm.server --model mlx-community/Qwen3.5-122B-A10B-8bit