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Can I run Qwen3-VL 32B locally?

Alibaba · 33.4B parameters · vision, chat, reasoning.

Ollama weight files: Q4_K_M 21 GB (qwen3-vl:32b); Q8_0 36 GB (qwen3-vl:32b-instruct-q8_0).

Yes on 60 machines in this list. The smallest is RTX 4060 Ti 16GB: Q4_K_M, about 23.6 GB, roughly 4 tokens per second, via Ollama. ollama run qwen3-vl:32b

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

Open Qwen3-VL 32B in the checker

Hardware that fits

HardwareRuntimeQuantMemoryFitSpeedCommand
RTX 4060 Ti 16GBOllamaQ4_K_M23.6 GBpartial offload (slower)~4 tok/sollama run qwen3-vl:32b
RTX 4070 Ti Super 16GBOllamaQ4_K_M23.6 GBpartial offload (slower)~5 tok/sollama run qwen3-vl:32b
RTX 4080 16GBOllamaQ4_K_M23.6 GBpartial offload (slower)~5 tok/sollama run qwen3-vl:32b
RTX 5080 16GBOllamaQ4_K_M23.6 GBpartial offload (slower)~5 tok/sollama run qwen3-vl:32b
RX 7800 XT 16GBOllamaQ4_K_M23.6 GBpartial offload (slower)~5 tok/sollama run qwen3-vl:32b
RX 9070 XT 16GBOllamaQ4_K_M23.6 GBpartial offload (slower)~5 tok/sollama run qwen3-vl:32b
RTX 3090 24GBLM StudioQ4_K_M GGUF22.4 GBfits in fast memory~28 tok/slms get unsloth/Qwen3-VL-32B-Instruct-GGUF@Q4_K_M
RTX 4090 24GBLM StudioQ4_K_M GGUF22.4 GBfits in fast memory~31 tok/slms get unsloth/Qwen3-VL-32B-Instruct-GGUF@Q4_K_M
RX 7900 XTX 24GBLM StudioQ4_K_M GGUF22.4 GBfits in fast memory~29 tok/slms get unsloth/Qwen3-VL-32B-Instruct-GGUF@Q4_K_M
M1 Max (24c GPU) 32GBOllamaQ4_K_M23.6 GBfits in fast memory~15 tok/sollama run qwen3-vl:32b
M1 Max (32c GPU) 32GBOllamaQ4_K_M23.6 GBfits in fast memory~15 tok/sollama run qwen3-vl:32b
M1 Pro 32GBOllamaQ4_K_M23.6 GBfits in fast memory~8 tok/sollama run qwen3-vl:32b
M2 Max (30c GPU) 32GBOllamaQ4_K_M23.6 GBfits in fast memory~15 tok/sollama run qwen3-vl:32b
M2 Max (38c GPU) 32GBOllamaQ4_K_M23.6 GBfits in fast memory~15 tok/sollama run qwen3-vl:32b
M2 Pro 32GBOllamaQ4_K_M23.6 GBfits in fast memory~8 tok/sollama run qwen3-vl:32b
M4 32GBOllamaQ4_K_M23.6 GBfits in fast memory~5 tok/sollama run qwen3-vl:32b
M3 Max (30c GPU) 36GBOllamaQ4_K_M23.6 GBfits in fast memory~11 tok/sollama run qwen3-vl:32b
M3 Pro 36GBOllamaQ4_K_M23.6 GBfits in fast memory~6 tok/sollama run qwen3-vl:32b
M4 Max (32c GPU) 36GBOllamaQ4_K_M23.6 GBfits in fast memory~16 tok/sollama run qwen3-vl:32b
Mac Studio M4 Max (32c GPU) 36GBOllamaQ4_K_M23.6 GBfits in fast memory~16 tok/sollama run qwen3-vl:32b
Mac Studio M5 Max (32c GPU) 36GBOllamaQ4_K_M23.6 GBfits in fast memory~18 tok/sollama run qwen3-vl:32b
RTX 5090 32GBOllamaQ4_K_M23.6 GBfits in fast memory~51 tok/sollama run qwen3-vl:32b
M3 Max (40c GPU) 48GBOllamaQ4_K_M23.6 GBfits in fast memory~15 tok/sollama run qwen3-vl:32b
M4 Max (40c GPU) 48GBOllamaQ4_K_M23.6 GBfits in fast memory~21 tok/sollama run qwen3-vl:32b
M4 Pro 48GBOllamaQ4_K_M23.6 GBfits in fast memory~10 tok/sollama run qwen3-vl:32b
Mac Studio M4 Max (40c GPU) 48GBOllamaQ4_K_M23.6 GBfits in fast memory~21 tok/sollama run qwen3-vl:32b
Mac Studio M5 Max (40c GPU) 48GBOllamaQ4_K_M23.6 GBfits in fast memory~23 tok/sollama run qwen3-vl:32b
M1 Max (32c GPU) 64GBOllamaQ8_038.6 GBfits in fast memory~9 tok/sollama run qwen3-vl:32b-instruct-q8_0
M2 Max (30c GPU) 64GBOllamaQ8_038.6 GBfits in fast memory~9 tok/sollama run qwen3-vl:32b-instruct-q8_0
M2 Max (38c GPU) 64GBOllamaQ8_038.6 GBfits in fast memory~9 tok/sollama run qwen3-vl:32b-instruct-q8_0
M2 Ultra 64GBOllamaQ8_038.6 GBfits in fast memory~18 tok/sollama run qwen3-vl:32b-instruct-q8_0
M3 Max (40c GPU) 64GBOllamaQ8_038.6 GBfits in fast memory~9 tok/sollama run qwen3-vl:32b-instruct-q8_0
M4 Max (40c GPU) 64GBOllamaQ8_038.6 GBfits in fast memory~12 tok/sollama run qwen3-vl:32b-instruct-q8_0
M4 Pro 64GBOllamaQ8_038.6 GBfits in fast memory~6 tok/sollama run qwen3-vl:32b-instruct-q8_0
Mac Studio M4 Max (40c GPU) 64GBOllamaQ8_038.6 GBfits in fast memory~12 tok/sollama run qwen3-vl:32b-instruct-q8_0
Mac Studio M5 Max (40c GPU) 64GBOllamaQ8_038.6 GBfits in fast memory~14 tok/sollama run qwen3-vl:32b-instruct-q8_0
M2 Max (38c GPU) 96GBOllamaQ8_038.6 GBfits in fast memory~9 tok/sollama run qwen3-vl:32b-instruct-q8_0
M3 Max (30c GPU) 96GBOllamaQ8_038.6 GBfits in fast memory~7 tok/sollama run qwen3-vl:32b-instruct-q8_0
Mac Studio M3 Ultra (60c GPU) 96GBOllamaQ8_038.6 GBfits in fast memory~18 tok/sollama run qwen3-vl:32b-instruct-q8_0
Mac Studio M3 Ultra (80c GPU) 96GBOllamaQ8_038.6 GBfits in fast memory~18 tok/sollama run qwen3-vl:32b-instruct-q8_0
Mac Studio M5 Ultra (64c GPU) 96GBOllamaQ8_038.6 GBfits in fast memory~27 tok/sollama run qwen3-vl:32b-instruct-q8_0
Mac Studio M5 Ultra (80c GPU) 96GBOllamaQ8_038.6 GBfits in fast memory~27 tok/sollama run qwen3-vl:32b-instruct-q8_0
M2 Ultra 128GBOllamaQ8_038.6 GBfits in fast memory~18 tok/sollama run qwen3-vl:32b-instruct-q8_0
M3 Max (40c GPU) 128GBOllamaQ8_038.6 GBfits in fast memory~9 tok/sollama run qwen3-vl:32b-instruct-q8_0
M4 Max (40c GPU) 128GBOllamaQ8_038.6 GBfits in fast memory~12 tok/sollama run qwen3-vl:32b-instruct-q8_0
Mac Studio M4 Max (40c GPU) 128GBOllamaQ8_038.6 GBfits in fast memory~12 tok/sollama run qwen3-vl:32b-instruct-q8_0
Mac Studio M5 Max (40c GPU) 128GBOllamaQ8_038.6 GBfits in fast memory~14 tok/sollama run qwen3-vl:32b-instruct-q8_0
DGX Spark 128GB (NVIDIA, ASUS, Dell, Lenovo, HP, MSI, Acer, Gigabyte)OllamaQ8_038.6 GBfits in fast memory~6 tok/sollama run qwen3-vl:32b-instruct-q8_0
M2 Ultra 192GBOllamaQ8_038.6 GBfits in fast memory~18 tok/sollama run qwen3-vl:32b-instruct-q8_0
2x Mac Studio M5 Max (40c GPU) 128GBllama.cppQ8_0 GGUF37.4 GBfits in fast memory~12 tok/sllama-server -hf unsloth/Qwen3-VL-32B-Instruct-GGUF:Q8_0 --rpc node2:50052 -c 8192 # run rpc-server on each other node
Mac Studio M3 Ultra (60c GPU) 256GBOllamaQ8_038.6 GBfits in fast memory~18 tok/sollama run qwen3-vl:32b-instruct-q8_0
Mac Studio M3 Ultra (80c GPU) 256GBOllamaQ8_038.6 GBfits in fast memory~18 tok/sollama run qwen3-vl:32b-instruct-q8_0
Mac Studio M5 Ultra (64c GPU) 256GBOllamaQ8_038.6 GBfits in fast memory~27 tok/sollama run qwen3-vl:32b-instruct-q8_0
Mac Studio M5 Ultra (80c GPU) 256GBOllamaQ8_038.6 GBfits in fast memory~27 tok/sollama run qwen3-vl:32b-instruct-q8_0
2x DGX Spark 128GBllama.cppQ8_0 GGUF37.4 GBfits in fast memory~5 tok/sllama-server -hf unsloth/Qwen3-VL-32B-Instruct-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 GGUF37.4 GBfits in fast memory~11 tok/sllama-server -hf unsloth/Qwen3-VL-32B-Instruct-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 GGUF37.4 GBfits in fast memory~23 tok/sllama-server -hf unsloth/Qwen3-VL-32B-Instruct-GGUF:Q8_0 --rpc node2:50052 -c 8192 # run rpc-server on each other node
Mac Studio M3 Ultra (80c GPU) 512GBOllamaQ8_038.6 GBfits in fast memory~18 tok/sollama run qwen3-vl:32b-instruct-q8_0
4x DGX Spark 128GBllama.cppQ8_0 GGUF37.4 GBfits in fast memory~4 tok/sllama-server -hf unsloth/Qwen3-VL-32B-Instruct-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 GGUF37.4 GBfits in fast memory~21 tok/sllama-server -hf unsloth/Qwen3-VL-32B-Instruct-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