← CanIRunLocal · All hardware · All models

Can I run Qwen 2.5 14B locally?

Alibaba · 14.8B parameters · chat.

Ollama weight files: Q4_K_M 9 GB (qwen2.5:14b); Q5_K_M 11 GB (qwen2.5:14b-instruct-q5_K_M); Q8_0 16 GB (qwen2.5:14b-instruct-q8_0).

Yes on 59 machines in this list. The smallest is RTX 3060 Ti 8GB: Q4_K_M, about 10.3 GB, roughly 12 tokens per second, via Ollama. ollama run qwen2.5:14b

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

Open Qwen 2.5 14B in the checker

Hardware that fits

HardwareRuntimeQuantMemoryFitSpeedCommand
RTX 3060 Ti 8GBOllamaQ4_K_M10.3 GBpartial offload (slower)~12 tok/sollama run qwen2.5:14b
RTX 3070 8GBOllamaQ4_K_M10.3 GBpartial offload (slower)~12 tok/sollama run qwen2.5:14b
RTX 4060 8GBOllamaQ4_K_M10.3 GBpartial offload (slower)~10 tok/sollama run qwen2.5:14b
RX 7600 8GBOllamaQ4_K_M10.3 GBpartial offload (slower)~10 tok/sollama run qwen2.5:14b
RTX 3080 10GBOllamaQ4_K_M10.3 GBpartial offload (slower)~28 tok/sollama run qwen2.5:14b
M1 16GBOllamaQ4_K_M10.3 GBfits in fast memory~6 tok/sollama run qwen2.5:14b
M2 16GBOllamaQ4_K_M10.3 GBfits in fast memory~9 tok/sollama run qwen2.5:14b
M3 16GBOllamaQ4_K_M10.3 GBfits in fast memory~9 tok/sollama run qwen2.5:14b
M4 16GBOllamaQ4_K_M10.3 GBfits in fast memory~11 tok/sollama run qwen2.5:14b
RTX 3060 12GBOllamaQ4_K_M10.3 GBfits in fast memory~24 tok/sollama run qwen2.5:14b
RTX 4070 12GBOllamaQ4_K_M10.3 GBfits in fast memory~34 tok/sollama run qwen2.5:14b
RTX 5070 12GBOllamaQ4_K_M10.3 GBfits in fast memory~45 tok/sollama run qwen2.5:14b
RTX 4060 Ti 16GBOllamaQ5_K_M12.3 GBfits in fast memory~16 tok/sollama run qwen2.5:14b-instruct-q5_K_M
RTX 4070 Ti Super 16GBOllamaQ5_K_M12.3 GBfits in fast memory~37 tok/sollama run qwen2.5:14b-instruct-q5_K_M
RTX 4080 16GBOllamaQ5_K_M12.3 GBfits in fast memory~39 tok/sollama run qwen2.5:14b-instruct-q5_K_M
RTX 5080 16GBOllamaQ5_K_M12.3 GBfits in fast memory~52 tok/sollama run qwen2.5:14b-instruct-q5_K_M
RX 7800 XT 16GBOllamaQ5_K_M12.3 GBfits in fast memory~34 tok/sollama run qwen2.5:14b-instruct-q5_K_M
RX 9070 XT 16GBOllamaQ5_K_M12.3 GBfits in fast memory~35 tok/sollama run qwen2.5:14b-instruct-q5_K_M
M2 24GBOllamaQ5_K_M12.3 GBfits in fast memory~7 tok/sollama run qwen2.5:14b-instruct-q5_K_M
M3 24GBOllamaQ5_K_M12.3 GBfits in fast memory~7 tok/sollama run qwen2.5:14b-instruct-q5_K_M
M4 24GBOllamaQ5_K_M12.3 GBfits in fast memory~9 tok/sollama run qwen2.5:14b-instruct-q5_K_M
RTX 3090 24GBOllamaQ8_017.3 GBfits in fast memory~35 tok/sollama run qwen2.5:14b-instruct-q8_0
RTX 4090 24GBOllamaQ8_017.3 GBfits in fast memory~38 tok/sollama run qwen2.5:14b-instruct-q8_0
RX 7900 XTX 24GBOllamaQ8_017.3 GBfits in fast memory~36 tok/sollama run qwen2.5:14b-instruct-q8_0
M1 Pro 32GBOllamaQ8_017.3 GBfits in fast memory~10 tok/sollama run qwen2.5:14b-instruct-q8_0
M2 Pro 32GBOllamaQ8_017.3 GBfits in fast memory~10 tok/sollama run qwen2.5:14b-instruct-q8_0
M4 32GBOllamaQ8_017.3 GBfits in fast memory~6 tok/sollama run qwen2.5:14b-instruct-q8_0
M3 Pro 36GBOllamaQ8_017.3 GBfits in fast memory~8 tok/sollama run qwen2.5:14b-instruct-q8_0
Mac Studio M4 Max (32c GPU) 36GBOllamaQ8_017.3 GBfits in fast memory~21 tok/sollama run qwen2.5:14b-instruct-q8_0
Mac Studio M5 Max (32c GPU) 36GBOllamaQ8_017.3 GBfits in fast memory~23 tok/sollama run qwen2.5:14b-instruct-q8_0
RTX 5090 32GBOllamaQ8_017.3 GBfits in fast memory~67 tok/sollama run qwen2.5:14b-instruct-q8_0
M4 Pro 48GBOllamaQ8_017.3 GBfits in fast memory~14 tok/sollama run qwen2.5:14b-instruct-q8_0
Mac Studio M4 Max (40c GPU) 48GBOllamaQ8_017.3 GBfits in fast memory~27 tok/sollama run qwen2.5:14b-instruct-q8_0
Mac Studio M5 Max (40c GPU) 48GBOllamaQ8_017.3 GBfits in fast memory~31 tok/sollama run qwen2.5:14b-instruct-q8_0
M1 Max 64GBOllamaQ8_017.3 GBfits in fast memory~20 tok/sollama run qwen2.5:14b-instruct-q8_0
M2 Max 64GBOllamaQ8_017.3 GBfits in fast memory~20 tok/sollama run qwen2.5:14b-instruct-q8_0
M3 Max 64GBOllamaQ8_017.3 GBfits in fast memory~20 tok/sollama run qwen2.5:14b-instruct-q8_0
M4 Max 64GBOllamaQ8_017.3 GBfits in fast memory~27 tok/sollama run qwen2.5:14b-instruct-q8_0
Mac Studio M4 Max (40c GPU) 64GBOllamaQ8_017.3 GBfits in fast memory~27 tok/sollama run qwen2.5:14b-instruct-q8_0
Mac Studio M5 Max (40c GPU) 64GBOllamaQ8_017.3 GBfits in fast memory~31 tok/sollama run qwen2.5:14b-instruct-q8_0
DGX Spark 64GB (ASUS, Dell, HP, MSI, Acer, Gigabyte)OllamaQ8_017.3 GBfits in fast memory~13 tok/sollama run qwen2.5:14b-instruct-q8_0
Mac Studio M3 Ultra 96GBOllamaQ8_017.3 GBfits in fast memory~41 tok/sollama run qwen2.5:14b-instruct-q8_0
Mac Studio M5 Ultra 96GBOllamaQ8_017.3 GBfits in fast memory~60 tok/sollama run qwen2.5:14b-instruct-q8_0
M3 Max 128GBOllamaQ8_017.3 GBfits in fast memory~20 tok/sollama run qwen2.5:14b-instruct-q8_0
M4 Max 128GBOllamaQ8_017.3 GBfits in fast memory~27 tok/sollama run qwen2.5:14b-instruct-q8_0
Mac Studio M4 Max (40c GPU) 128GBOllamaQ8_017.3 GBfits in fast memory~27 tok/sollama run qwen2.5:14b-instruct-q8_0
Mac Studio M5 Max (40c GPU) 128GBOllamaQ8_017.3 GBfits in fast memory~31 tok/sollama run qwen2.5:14b-instruct-q8_0
DGX Spark 128GB (NVIDIA, ASUS, Dell, Lenovo, HP, MSI, Acer, Gigabyte)OllamaQ8_017.3 GBfits in fast memory~13 tok/sollama run qwen2.5:14b-instruct-q8_0
M2 Ultra 192GBOllamaQ8_017.3 GBfits in fast memory~40 tok/sollama run qwen2.5:14b-instruct-q8_0
2x Mac Studio M5 Max (40c GPU) 128GBllama.cppQ8_0 GGUF17 GBfits in fast memory~27 tok/sllama-server -hf bartowski/Qwen2.5-14B-Instruct-GGUF:Q8_0 --rpc node2:50052 -c 8192 # run rpc-server on each other node
Mac Studio M3 Ultra 256GBOllamaQ8_017.3 GBfits in fast memory~41 tok/sollama run qwen2.5:14b-instruct-q8_0
Mac Studio M5 Ultra (64c GPU) 256GBOllamaQ8_017.3 GBfits in fast memory~60 tok/sollama run qwen2.5:14b-instruct-q8_0
Mac Studio M5 Ultra (80c GPU) 256GBOllamaQ8_017.3 GBfits in fast memory~60 tok/sollama run qwen2.5:14b-instruct-q8_0
2x DGX Spark 128GBllama.cppQ8_0 GGUF17 GBfits in fast memory~11 tok/sllama-server -hf bartowski/Qwen2.5-14B-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 GGUF17 GBfits in fast memory~23 tok/sllama-server -hf bartowski/Qwen2.5-14B-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 GGUF17 GBfits in fast memory~52 tok/sllama-server -hf bartowski/Qwen2.5-14B-Instruct-GGUF:Q8_0 --rpc node2:50052 -c 8192 # run rpc-server on each other node
Mac Studio M3 Ultra (80c GPU) 512GBOllamaQ8_017.3 GBfits in fast memory~41 tok/sollama run qwen2.5:14b-instruct-q8_0
4x DGX Spark 128GBllama.cppQ8_0 GGUF17 GBfits in fast memory~10 tok/sllama-server -hf bartowski/Qwen2.5-14B-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 GGUF17 GBfits in fast memory~46 tok/sllama-server -hf bartowski/Qwen2.5-14B-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 2026-10-16.

A project by OnDevice Labs · llms.txt