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Can I run Qwen3 0.6B locally?

Alibaba · 0.75B parameters · chat, reasoning.

Ollama weight files: Q4_K_M 0.52 GB (qwen3:0.6b); Q8_0 0.83 GB (qwen3:0.6b-q8_0).

Yes on 62 machines in this list. The smallest is M1 8GB: Q8_0, about 1.5 GB, roughly 66 tokens per second, via Ollama. ollama run qwen3:0.6b-q8_0

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

Open Qwen3 0.6B in the checker

Hardware that fits

HardwareRuntimeQuantMemoryFitSpeedCommand
M1 8GBOllamaQ8_01.5 GBfits in fast memory~66 tok/sollama run qwen3:0.6b-q8_0
M2 8GBOllamaQ8_01.5 GBfits in fast memory~96 tok/sollama run qwen3:0.6b-q8_0
M3 8GBOllamaQ8_01.5 GBfits in fast memory~96 tok/sollama run qwen3:0.6b-q8_0
RTX 3060 Ti 8GBOllamaQ8_01.5 GBfits in fast memory~324 tok/sollama run qwen3:0.6b-q8_0
RTX 3070 8GBOllamaQ8_01.5 GBfits in fast memory~324 tok/sollama run qwen3:0.6b-q8_0
RTX 4060 8GBOllamaQ8_01.5 GBfits in fast memory~197 tok/sollama run qwen3:0.6b-q8_0
RX 7600 8GBOllamaQ8_01.5 GBfits in fast memory~208 tok/sollama run qwen3:0.6b-q8_0
RTX 3080 10GBOllamaQ8_01.5 GBfits in fast memory~549 tok/sollama run qwen3:0.6b-q8_0
M1 16GBOllamaQ8_01.5 GBfits in fast memory~66 tok/sollama run qwen3:0.6b-q8_0
M2 16GBOllamaQ8_01.5 GBfits in fast memory~96 tok/sollama run qwen3:0.6b-q8_0
M3 16GBOllamaQ8_01.5 GBfits in fast memory~96 tok/sollama run qwen3:0.6b-q8_0
M4 16GBOllamaQ8_01.5 GBfits in fast memory~116 tok/sollama run qwen3:0.6b-q8_0
RTX 3060 12GBOllamaQ8_01.5 GBfits in fast memory~260 tok/sollama run qwen3:0.6b-q8_0
RTX 4070 12GBOllamaQ8_01.5 GBfits in fast memory~364 tok/sollama run qwen3:0.6b-q8_0
RTX 5070 12GBOllamaQ8_01.5 GBfits in fast memory~486 tok/sollama run qwen3:0.6b-q8_0
RTX 4060 Ti 16GBOllamaQ8_01.5 GBfits in fast memory~208 tok/sollama run qwen3:0.6b-q8_0
RTX 4070 Ti Super 16GBOllamaQ8_01.5 GBfits in fast memory~486 tok/sollama run qwen3:0.6b-q8_0
RTX 4080 16GBOllamaQ8_01.5 GBfits in fast memory~518 tok/sollama run qwen3:0.6b-q8_0
RTX 5080 16GBOllamaQ8_01.5 GBfits in fast memory~694 tok/sollama run qwen3:0.6b-q8_0
RX 7800 XT 16GBOllamaQ8_01.5 GBfits in fast memory~451 tok/sollama run qwen3:0.6b-q8_0
RX 9070 XT 16GBOllamaQ8_01.5 GBfits in fast memory~463 tok/sollama run qwen3:0.6b-q8_0
M2 24GBOllamaQ8_01.5 GBfits in fast memory~96 tok/sollama run qwen3:0.6b-q8_0
M3 24GBOllamaQ8_01.5 GBfits in fast memory~96 tok/sollama run qwen3:0.6b-q8_0
M4 24GBOllamaQ8_01.5 GBfits in fast memory~116 tok/sollama run qwen3:0.6b-q8_0
RTX 3090 24GBOllamaQ8_01.5 GBfits in fast memory~677 tok/sollama run qwen3:0.6b-q8_0
RTX 4090 24GBOllamaQ8_01.5 GBfits in fast memory~729 tok/sollama run qwen3:0.6b-q8_0
RX 7900 XTX 24GBOllamaQ8_01.5 GBfits in fast memory~694 tok/sollama run qwen3:0.6b-q8_0
M1 Pro 32GBOllamaQ8_01.5 GBfits in fast memory~193 tok/sollama run qwen3:0.6b-q8_0
M2 Pro 32GBOllamaQ8_01.5 GBfits in fast memory~193 tok/sollama run qwen3:0.6b-q8_0
M4 32GBOllamaQ8_01.5 GBfits in fast memory~116 tok/sollama run qwen3:0.6b-q8_0
M3 Pro 36GBOllamaQ8_01.5 GBfits in fast memory~145 tok/sollama run qwen3:0.6b-q8_0
Mac Studio M4 Max (32c GPU) 36GBOllamaQ8_01.5 GBfits in fast memory~395 tok/sollama run qwen3:0.6b-q8_0
Mac Studio M5 Max (32c GPU) 36GBOllamaQ8_01.5 GBfits in fast memory~443 tok/sollama run qwen3:0.6b-q8_0
RTX 5090 32GBOllamaQ8_01.5 GBfits in fast memory~1295 tok/sollama run qwen3:0.6b-q8_0
M4 Pro 48GBOllamaQ8_01.5 GBfits in fast memory~263 tok/sollama run qwen3:0.6b-q8_0
Mac Studio M4 Max (40c GPU) 48GBOllamaQ8_01.5 GBfits in fast memory~526 tok/sollama run qwen3:0.6b-q8_0
Mac Studio M5 Max (40c GPU) 48GBOllamaQ8_01.5 GBfits in fast memory~592 tok/sollama run qwen3:0.6b-q8_0
M1 Max 64GBOllamaQ8_01.5 GBfits in fast memory~386 tok/sollama run qwen3:0.6b-q8_0
M2 Max 64GBOllamaQ8_01.5 GBfits in fast memory~386 tok/sollama run qwen3:0.6b-q8_0
M3 Max 64GBOllamaQ8_01.5 GBfits in fast memory~386 tok/sollama run qwen3:0.6b-q8_0
M4 Max 64GBOllamaQ8_01.5 GBfits in fast memory~526 tok/sollama run qwen3:0.6b-q8_0
Mac Studio M4 Max (40c GPU) 64GBOllamaQ8_01.5 GBfits in fast memory~526 tok/sollama run qwen3:0.6b-q8_0
Mac Studio M5 Max (40c GPU) 64GBOllamaQ8_01.5 GBfits in fast memory~592 tok/sollama run qwen3:0.6b-q8_0
DGX Spark 64GB (ASUS, Dell, HP, MSI, Acer, Gigabyte)OllamaQ8_01.5 GBfits in fast memory~247 tok/sollama run qwen3:0.6b-q8_0
Mac Studio M3 Ultra 96GBOllamaQ8_01.5 GBfits in fast memory~789 tok/sollama run qwen3:0.6b-q8_0
Mac Studio M5 Ultra 96GBOllamaQ8_01.5 GBfits in fast memory~1157 tok/sollama run qwen3:0.6b-q8_0
M3 Max 128GBOllamaQ8_01.5 GBfits in fast memory~386 tok/sollama run qwen3:0.6b-q8_0
M4 Max 128GBOllamaQ8_01.5 GBfits in fast memory~526 tok/sollama run qwen3:0.6b-q8_0
Mac Studio M4 Max (40c GPU) 128GBOllamaQ8_01.5 GBfits in fast memory~526 tok/sollama run qwen3:0.6b-q8_0
Mac Studio M5 Max (40c GPU) 128GBOllamaQ8_01.5 GBfits in fast memory~592 tok/sollama run qwen3:0.6b-q8_0
DGX Spark 128GB (NVIDIA, ASUS, Dell, Lenovo, HP, MSI, Acer, Gigabyte)OllamaQ8_01.5 GBfits in fast memory~247 tok/sollama run qwen3:0.6b-q8_0
M2 Ultra 192GBOllamaQ8_01.5 GBfits in fast memory~771 tok/sollama run qwen3:0.6b-q8_0
2x Mac Studio M5 Max (40c GPU) 128GBllama.cppQ8_0 GGUF1.3 GBfits in fast memory~652 tok/sllama-server -hf unsloth/Qwen3-0.6B-GGUF:Q8_0 --rpc node2:50052 -c 8192 # run rpc-server on each other node
Mac Studio M3 Ultra 256GBOllamaQ8_01.5 GBfits in fast memory~789 tok/sollama run qwen3:0.6b-q8_0
Mac Studio M5 Ultra (64c GPU) 256GBOllamaQ8_01.5 GBfits in fast memory~1157 tok/sollama run qwen3:0.6b-q8_0
Mac Studio M5 Ultra (80c GPU) 256GBOllamaQ8_01.5 GBfits in fast memory~1157 tok/sollama run qwen3:0.6b-q8_0
2x DGX Spark 128GBllama.cppQ8_0 GGUF1.3 GBfits in fast memory~272 tok/sllama-server -hf unsloth/Qwen3-0.6B-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 GGUF1.3 GBfits in fast memory~576 tok/sllama-server -hf unsloth/Qwen3-0.6B-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 GGUF1.3 GBfits in fast memory~1275 tok/sllama-server -hf unsloth/Qwen3-0.6B-GGUF:Q8_0 --rpc node2:50052 -c 8192 # run rpc-server on each other node
Mac Studio M3 Ultra (80c GPU) 512GBOllamaQ8_01.5 GBfits in fast memory~789 tok/sollama run qwen3:0.6b-q8_0
4x DGX Spark 128GBllama.cppQ8_0 GGUF1.3 GBfits in fast memory~240 tok/sllama-server -hf unsloth/Qwen3-0.6B-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 GGUF1.3 GBfits in fast memory~1125 tok/sllama-server -hf unsloth/Qwen3-0.6B-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 2026-10-16.

A project by OnDevice Labs · llms.txt