← CanIRunLocal · All hardware · All models

Can I run Phi-4 14B locally?

Microsoft · 14.7B parameters · chat, reasoning.

Ollama weight files: Q4_K_M 9.1 GB (phi4:14b); Q8_0 16 GB (phi4:14b-q8_0).

Yes on 59 machines in this list. The smallest is RTX 3060 Ti 8GB: Q4_K_M, about 10.4 GB, roughly 11 tokens per second, via Ollama. ollama run phi4:14b

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

Open Phi-4 14B in the checker

Hardware that fits

HardwareRuntimeQuantMemoryFitSpeedCommand
RTX 3060 Ti 8GBOllamaQ4_K_M10.4 GBpartial offload (slower)~11 tok/sollama run phi4:14b
RTX 3070 8GBOllamaQ4_K_M10.4 GBpartial offload (slower)~11 tok/sollama run phi4:14b
RTX 4060 8GBOllamaQ4_K_M10.4 GBpartial offload (slower)~10 tok/sollama run phi4:14b
RX 7600 8GBOllamaQ4_K_M10.4 GBpartial offload (slower)~10 tok/sollama run phi4:14b
RTX 3080 10GBOllamaQ4_K_M10.4 GBpartial offload (slower)~26 tok/sollama run phi4:14b
M1 16GBOllamaQ4_K_M10.4 GBfits in fast memory~6 tok/sollama run phi4:14b
M2 16GBOllamaQ4_K_M10.4 GBfits in fast memory~9 tok/sollama run phi4:14b
M3 16GBOllamaQ4_K_M10.4 GBfits in fast memory~9 tok/sollama run phi4:14b
M4 16GBOllamaQ4_K_M10.4 GBfits in fast memory~11 tok/sollama run phi4:14b
RTX 3060 12GBOllamaQ4_K_M10.4 GBfits in fast memory~24 tok/sollama run phi4:14b
RTX 4070 12GBOllamaQ4_K_M10.4 GBfits in fast memory~33 tok/sollama run phi4:14b
RTX 5070 12GBOllamaQ4_K_M10.4 GBfits in fast memory~44 tok/sollama run phi4:14b
RTX 4060 Ti 16GBOllamaQ4_K_M10.4 GBfits in fast memory~19 tok/sollama run phi4:14b
RTX 4070 Ti Super 16GBOllamaQ4_K_M10.4 GBfits in fast memory~44 tok/sollama run phi4:14b
RTX 4080 16GBOllamaQ4_K_M10.4 GBfits in fast memory~47 tok/sollama run phi4:14b
RTX 5080 16GBOllamaQ4_K_M10.4 GBfits in fast memory~63 tok/sollama run phi4:14b
RX 7800 XT 16GBOllamaQ4_K_M10.4 GBfits in fast memory~41 tok/sollama run phi4:14b
RX 9070 XT 16GBOllamaQ4_K_M10.4 GBfits in fast memory~42 tok/sollama run phi4:14b
M2 24GBOllamaQ4_K_M10.4 GBfits in fast memory~9 tok/sollama run phi4:14b
M3 24GBOllamaQ4_K_M10.4 GBfits in fast memory~9 tok/sollama run phi4:14b
M4 24GBOllamaQ4_K_M10.4 GBfits in fast memory~11 tok/sollama run phi4:14b
RTX 3090 24GBOllamaQ8_017.3 GBfits in fast memory~35 tok/sollama run phi4:14b-q8_0
RTX 4090 24GBOllamaQ8_017.3 GBfits in fast memory~38 tok/sollama run phi4:14b-q8_0
RX 7900 XTX 24GBOllamaQ8_017.3 GBfits in fast memory~36 tok/sollama run phi4:14b-q8_0
M1 Pro 32GBOllamaQ8_017.3 GBfits in fast memory~10 tok/sollama run phi4:14b-q8_0
M2 Pro 32GBOllamaQ8_017.3 GBfits in fast memory~10 tok/sollama run phi4:14b-q8_0
M4 32GBOllamaQ8_017.3 GBfits in fast memory~6 tok/sollama run phi4:14b-q8_0
M3 Pro 36GBOllamaQ8_017.3 GBfits in fast memory~8 tok/sollama run phi4:14b-q8_0
Mac Studio M4 Max (32c GPU) 36GBOllamaQ8_017.3 GBfits in fast memory~21 tok/sollama run phi4:14b-q8_0
Mac Studio M5 Max (32c GPU) 36GBOllamaQ8_017.3 GBfits in fast memory~23 tok/sollama run phi4:14b-q8_0
RTX 5090 32GBOllamaQ8_017.3 GBfits in fast memory~67 tok/sollama run phi4:14b-q8_0
M4 Pro 48GBOllamaQ8_017.3 GBfits in fast memory~14 tok/sollama run phi4:14b-q8_0
Mac Studio M4 Max (40c GPU) 48GBOllamaQ8_017.3 GBfits in fast memory~27 tok/sollama run phi4:14b-q8_0
Mac Studio M5 Max (40c GPU) 48GBOllamaQ8_017.3 GBfits in fast memory~31 tok/sollama run phi4:14b-q8_0
M1 Max 64GBOllamaQ8_017.3 GBfits in fast memory~20 tok/sollama run phi4:14b-q8_0
M2 Max 64GBOllamaQ8_017.3 GBfits in fast memory~20 tok/sollama run phi4:14b-q8_0
M3 Max 64GBOllamaQ8_017.3 GBfits in fast memory~20 tok/sollama run phi4:14b-q8_0
M4 Max 64GBOllamaQ8_017.3 GBfits in fast memory~27 tok/sollama run phi4:14b-q8_0
Mac Studio M4 Max (40c GPU) 64GBOllamaQ8_017.3 GBfits in fast memory~27 tok/sollama run phi4:14b-q8_0
Mac Studio M5 Max (40c GPU) 64GBOllamaQ8_017.3 GBfits in fast memory~31 tok/sollama run phi4:14b-q8_0
DGX Spark 64GB (ASUS, Dell, HP, MSI, Acer, Gigabyte)OllamaQ8_017.3 GBfits in fast memory~13 tok/sollama run phi4:14b-q8_0
Mac Studio M3 Ultra 96GBOllamaQ8_017.3 GBfits in fast memory~41 tok/sollama run phi4:14b-q8_0
Mac Studio M5 Ultra 96GBOllamaQ8_017.3 GBfits in fast memory~60 tok/sollama run phi4:14b-q8_0
M3 Max 128GBOllamaQ8_017.3 GBfits in fast memory~20 tok/sollama run phi4:14b-q8_0
M4 Max 128GBOllamaQ8_017.3 GBfits in fast memory~27 tok/sollama run phi4:14b-q8_0
Mac Studio M4 Max (40c GPU) 128GBOllamaQ8_017.3 GBfits in fast memory~27 tok/sollama run phi4:14b-q8_0
Mac Studio M5 Max (40c GPU) 128GBOllamaQ8_017.3 GBfits in fast memory~31 tok/sollama run phi4:14b-q8_0
DGX Spark 128GB (NVIDIA, ASUS, Dell, Lenovo, HP, MSI, Acer, Gigabyte)OllamaQ8_017.3 GBfits in fast memory~13 tok/sollama run phi4:14b-q8_0
M2 Ultra 192GBOllamaQ8_017.3 GBfits in fast memory~40 tok/sollama run phi4:14b-q8_0
2x Mac Studio M5 Max (40c GPU) 128GBllama.cppQ8_0 GGUF16.9 GBfits in fast memory~27 tok/sllama-server -hf unsloth/phi-4-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 phi4:14b-q8_0
Mac Studio M5 Ultra (64c GPU) 256GBOllamaQ8_017.3 GBfits in fast memory~60 tok/sollama run phi4:14b-q8_0
Mac Studio M5 Ultra (80c GPU) 256GBOllamaQ8_017.3 GBfits in fast memory~60 tok/sollama run phi4:14b-q8_0
2x DGX Spark 128GBllama.cppQ8_0 GGUF16.9 GBfits in fast memory~11 tok/sllama-server -hf unsloth/phi-4-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 GGUF16.9 GBfits in fast memory~24 tok/sllama-server -hf unsloth/phi-4-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 GGUF16.9 GBfits in fast memory~52 tok/sllama-server -hf unsloth/phi-4-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 phi4:14b-q8_0
4x DGX Spark 128GBllama.cppQ8_0 GGUF16.9 GBfits in fast memory~10 tok/sllama-server -hf unsloth/phi-4-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 GGUF16.9 GBfits in fast memory~46 tok/sllama-server -hf unsloth/phi-4-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