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Can I run Qwen3.5 4B locally?

Alibaba · 4.66B parameters · chat, reasoning, coding, vision.

Ollama weight files: Q4_K_M 3.3 GB (qwen3.5:4b-q4_K_M); Q8_0 5.2 GB (qwen3.5:4b-q8_0).

Yes on 62 machines in this list. The smallest is M1 8GB: Q4_K_M, about 4.5 GB, roughly 16 tokens per second, via Ollama. ollama run qwen3.5:4b-q4_K_M

Setup on DGX Spark 128GB (NVIDIA, ASUS, Dell, Lenovo, HP, MSI, Acer, Gigabyte)

Open Qwen3.5 4B in the checker

Hardware that fits

HardwareRuntimeQuantMemoryFitSpeedCommand
M1 8GBOllamaQ4_K_M4.5 GBfits in fast memory~16 tok/sollama run qwen3.5:4b-q4_K_M
M2 8GBOllamaQ4_K_M4.5 GBfits in fast memory~24 tok/sollama run qwen3.5:4b-q4_K_M
M3 8GBOllamaQ4_K_M4.5 GBfits in fast memory~24 tok/sollama run qwen3.5:4b-q4_K_M
RTX 3060 Ti 8GBOllamaQ8_06.4 GBfits in fast memory~52 tok/sollama run qwen3.5:4b-q8_0
RTX 3070 8GBOllamaQ8_06.4 GBfits in fast memory~52 tok/sollama run qwen3.5:4b-q8_0
RTX 4060 8GBOllamaQ8_06.4 GBfits in fast memory~31 tok/sollama run qwen3.5:4b-q8_0
RX 7600 8GBOllamaQ8_06.4 GBfits in fast memory~33 tok/sollama run qwen3.5:4b-q8_0
RTX 3080 10GBOllamaQ8_06.4 GBfits in fast memory~88 tok/sollama run qwen3.5:4b-q8_0
M1 16GBOllamaQ8_06.4 GBfits in fast memory~10 tok/sollama run qwen3.5:4b-q8_0
M2 16GBOllamaQ8_06.4 GBfits in fast memory~15 tok/sollama run qwen3.5:4b-q8_0
M3 16GBOllamaQ8_06.4 GBfits in fast memory~15 tok/sollama run qwen3.5:4b-q8_0
M4 16GBOllamaQ8_06.4 GBfits in fast memory~18 tok/sollama run qwen3.5:4b-q8_0
RTX 3060 12GBOllamaQ8_06.4 GBfits in fast memory~42 tok/sollama run qwen3.5:4b-q8_0
RTX 4070 12GBOllamaQ8_06.4 GBfits in fast memory~58 tok/sollama run qwen3.5:4b-q8_0
RTX 5070 12GBOllamaQ8_06.4 GBfits in fast memory~78 tok/sollama run qwen3.5:4b-q8_0
RTX 4060 Ti 16GBOllamaQ8_06.4 GBfits in fast memory~33 tok/sollama run qwen3.5:4b-q8_0
RTX 4070 Ti Super 16GBOllamaQ8_06.4 GBfits in fast memory~78 tok/sollama run qwen3.5:4b-q8_0
RTX 4080 16GBOllamaQ8_06.4 GBfits in fast memory~83 tok/sollama run qwen3.5:4b-q8_0
RTX 5080 16GBOllamaQ8_06.4 GBfits in fast memory~111 tok/sollama run qwen3.5:4b-q8_0
RX 7800 XT 16GBOllamaQ8_06.4 GBfits in fast memory~72 tok/sollama run qwen3.5:4b-q8_0
RX 9070 XT 16GBOllamaQ8_06.4 GBfits in fast memory~74 tok/sollama run qwen3.5:4b-q8_0
M2 24GBOllamaQ8_06.4 GBfits in fast memory~15 tok/sollama run qwen3.5:4b-q8_0
M3 24GBOllamaQ8_06.4 GBfits in fast memory~15 tok/sollama run qwen3.5:4b-q8_0
M4 24GBOllamaQ8_06.4 GBfits in fast memory~18 tok/sollama run qwen3.5:4b-q8_0
RTX 3090 24GBOllamaQ8_06.4 GBfits in fast memory~108 tok/sollama run qwen3.5:4b-q8_0
RTX 4090 24GBOllamaQ8_06.4 GBfits in fast memory~116 tok/sollama run qwen3.5:4b-q8_0
RX 7900 XTX 24GBOllamaQ8_06.4 GBfits in fast memory~111 tok/sollama run qwen3.5:4b-q8_0
M1 Pro 32GBOllamaQ8_06.4 GBfits in fast memory~31 tok/sollama run qwen3.5:4b-q8_0
M2 Pro 32GBOllamaQ8_06.4 GBfits in fast memory~31 tok/sollama run qwen3.5:4b-q8_0
M4 32GBOllamaQ8_06.4 GBfits in fast memory~18 tok/sollama run qwen3.5:4b-q8_0
M3 Pro 36GBOllamaQ8_06.4 GBfits in fast memory~23 tok/sollama run qwen3.5:4b-q8_0
Mac Studio M4 Max (32c GPU) 36GBOllamaQ8_06.4 GBfits in fast memory~63 tok/sollama run qwen3.5:4b-q8_0
Mac Studio M5 Max (32c GPU) 36GBOllamaQ8_06.4 GBfits in fast memory~71 tok/sollama run qwen3.5:4b-q8_0
RTX 5090 32GBOllamaQ8_06.4 GBfits in fast memory~207 tok/sollama run qwen3.5:4b-q8_0
M4 Pro 48GBOllamaQ8_06.4 GBfits in fast memory~42 tok/sollama run qwen3.5:4b-q8_0
Mac Studio M4 Max (40c GPU) 48GBOllamaQ8_06.4 GBfits in fast memory~84 tok/sollama run qwen3.5:4b-q8_0
Mac Studio M5 Max (40c GPU) 48GBOllamaQ8_06.4 GBfits in fast memory~94 tok/sollama run qwen3.5:4b-q8_0
M1 Max 64GBOllamaQ8_06.4 GBfits in fast memory~62 tok/sollama run qwen3.5:4b-q8_0
M2 Max 64GBOllamaQ8_06.4 GBfits in fast memory~62 tok/sollama run qwen3.5:4b-q8_0
M3 Max 64GBOllamaQ8_06.4 GBfits in fast memory~62 tok/sollama run qwen3.5:4b-q8_0
M4 Max 64GBOllamaQ8_06.4 GBfits in fast memory~84 tok/sollama run qwen3.5:4b-q8_0
Mac Studio M4 Max (40c GPU) 64GBOllamaQ8_06.4 GBfits in fast memory~84 tok/sollama run qwen3.5:4b-q8_0
Mac Studio M5 Max (40c GPU) 64GBOllamaQ8_06.4 GBfits in fast memory~94 tok/sollama run qwen3.5:4b-q8_0
DGX Spark 64GB (ASUS, Dell, HP, MSI, Acer, Gigabyte)OllamaQ8_06.4 GBfits in fast memory~39 tok/sollama run qwen3.5:4b-q8_0
Mac Studio M3 Ultra 96GBOllamaQ8_06.4 GBfits in fast memory~126 tok/sollama run qwen3.5:4b-q8_0
Mac Studio M5 Ultra 96GBOllamaQ8_06.4 GBfits in fast memory~185 tok/sollama run qwen3.5:4b-q8_0
M3 Max 128GBOllamaQ8_06.4 GBfits in fast memory~62 tok/sollama run qwen3.5:4b-q8_0
M4 Max 128GBOllamaQ8_06.4 GBfits in fast memory~84 tok/sollama run qwen3.5:4b-q8_0
Mac Studio M4 Max (40c GPU) 128GBOllamaQ8_06.4 GBfits in fast memory~84 tok/sollama run qwen3.5:4b-q8_0
Mac Studio M5 Max (40c GPU) 128GBOllamaQ8_06.4 GBfits in fast memory~94 tok/sollama run qwen3.5:4b-q8_0
DGX Spark 128GB (NVIDIA, ASUS, Dell, Lenovo, HP, MSI, Acer, Gigabyte)OllamaQ8_06.4 GBfits in fast memory~39 tok/sollama run qwen3.5:4b-q8_0
M2 Ultra 192GBOllamaQ8_06.4 GBfits in fast memory~123 tok/sollama run qwen3.5:4b-q8_0
2x Mac Studio M5 Max (40c GPU) 128GBllama.cppQ8_0 GGUF5.7 GBfits in fast memory~93 tok/sllama-server -hf unsloth/Qwen3.5-4B-GGUF:Q8_0 --rpc node2:50052 -c 8192 # run rpc-server on each other node
Mac Studio M3 Ultra 256GBOllamaQ8_06.4 GBfits in fast memory~126 tok/sollama run qwen3.5:4b-q8_0
Mac Studio M5 Ultra (64c GPU) 256GBOllamaQ8_06.4 GBfits in fast memory~185 tok/sollama run qwen3.5:4b-q8_0
Mac Studio M5 Ultra (80c GPU) 256GBOllamaQ8_06.4 GBfits in fast memory~185 tok/sollama run qwen3.5:4b-q8_0
2x DGX Spark 128GBllama.cppQ8_0 GGUF5.7 GBfits in fast memory~39 tok/sllama-server -hf unsloth/Qwen3.5-4B-GGUF:Q8_0 --rpc node2:50052 -c 8192 # run rpc-server on each other node
4x Mac Studio M5 Max (40c GPU) 128GBllama.cppQ8_0 GGUF5.7 GBfits in fast memory~82 tok/sllama-server -hf unsloth/Qwen3.5-4B-GGUF:Q8_0 --rpc node2:50052,node3:50052,node4:50052 -c 8192 # run rpc-server on each other node
2x Mac Studio M5 Ultra (80c GPU) 256GBllama.cppQ8_0 GGUF5.7 GBfits in fast memory~182 tok/sllama-server -hf unsloth/Qwen3.5-4B-GGUF:Q8_0 --rpc node2:50052 -c 8192 # run rpc-server on each other node
Mac Studio M3 Ultra (80c GPU) 512GBOllamaQ8_06.4 GBfits in fast memory~126 tok/sollama run qwen3.5:4b-q8_0
4x DGX Spark 128GBllama.cppQ8_0 GGUF5.7 GBfits in fast memory~34 tok/sllama-server -hf unsloth/Qwen3.5-4B-GGUF:Q8_0 --rpc node2:50052,node3:50052,node4:50052 -c 8192 # run rpc-server on each other node
4x Mac Studio M5 Ultra (80c GPU) 256GBllama.cppQ8_0 GGUF5.7 GBfits in fast memory~161 tok/sllama-server -hf unsloth/Qwen3.5-4B-GGUF:Q8_0 --rpc node2:50052,node3:50052,node4:50052 -c 8192 # run rpc-server on each other node

Estimates, not benchmarks. Model sizes are ollama.com download sizes; memory needed adds headroom for ~8k tokens of context; speeds are rough figures from memory bandwidth. Data updated 2026-10-18.

A project by OnDevice Labs · llms.txt