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Can I run Gemma 4 31B locally?

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Ollama weight files: Q4_K_M 20 GB (gemma4:31b-it-q4_K_M); Q8_0 34 GB (gemma4:31b-it-q8_0).

Yes on 47 machines in this list. The smallest is RTX 3060 12GB: Q4_K_M, about 20.8 GB, roughly 4 tokens per second, via LM Studio. lms get unsloth/gemma-4-31B-it-GGUF@Q4_K_M

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

Open Gemma 4 31B in the checker

Hardware that fits

HardwareRuntimeQuantMemoryFitSpeedCommand
RTX 3060 12GBLM StudioQ4_K_M GGUF20.8 GBpartial offload (slower)~4 tok/slms get unsloth/gemma-4-31B-it-GGUF@Q4_K_M
RTX 4070 12GBLM StudioQ4_K_M GGUF20.8 GBpartial offload (slower)~4 tok/slms get unsloth/gemma-4-31B-it-GGUF@Q4_K_M
RTX 5070 12GBLM StudioQ4_K_M GGUF20.8 GBpartial offload (slower)~4 tok/slms get unsloth/gemma-4-31B-it-GGUF@Q4_K_M
RTX 4060 Ti 16GBOllamaQ4_K_M22.5 GBpartial offload (slower)~4 tok/sollama run gemma4:31b-it-q4_K_M
RTX 4070 Ti Super 16GBOllamaQ4_K_M22.5 GBpartial offload (slower)~5 tok/sollama run gemma4:31b-it-q4_K_M
RTX 4080 16GBOllamaQ4_K_M22.5 GBpartial offload (slower)~5 tok/sollama run gemma4:31b-it-q4_K_M
RTX 5080 16GBOllamaQ4_K_M22.5 GBpartial offload (slower)~6 tok/sollama run gemma4:31b-it-q4_K_M
RX 7800 XT 16GBOllamaQ4_K_M22.5 GBpartial offload (slower)~5 tok/sollama run gemma4:31b-it-q4_K_M
RX 9070 XT 16GBOllamaQ4_K_M22.5 GBpartial offload (slower)~5 tok/sollama run gemma4:31b-it-q4_K_M
RTX 3090 24GBOllamaQ4_K_M22.5 GBfits in fast memory~28 tok/sollama run gemma4:31b-it-q4_K_M
RTX 4090 24GBOllamaQ4_K_M22.5 GBfits in fast memory~30 tok/sollama run gemma4:31b-it-q4_K_M
RX 7900 XTX 24GBOllamaQ4_K_M22.5 GBfits in fast memory~29 tok/sollama run gemma4:31b-it-q4_K_M
M1 Pro 32GBOllamaQ4_K_M22.5 GBfits in fast memory~8 tok/sollama run gemma4:31b-it-q4_K_M
M2 Pro 32GBOllamaQ4_K_M22.5 GBfits in fast memory~8 tok/sollama run gemma4:31b-it-q4_K_M
M4 32GBOllamaQ4_K_M22.5 GBfits in fast memory~5 tok/sollama run gemma4:31b-it-q4_K_M
M3 Pro 36GBOllamaQ4_K_M22.5 GBfits in fast memory~6 tok/sollama run gemma4:31b-it-q4_K_M
Mac Studio M4 Max (32c GPU) 36GBOllamaQ4_K_M22.5 GBfits in fast memory~16 tok/sollama run gemma4:31b-it-q4_K_M
Mac Studio M5 Max (32c GPU) 36GBOllamaQ4_K_M22.5 GBfits in fast memory~18 tok/sollama run gemma4:31b-it-q4_K_M
RTX 5090 32GBOllamaQ4_K_M22.5 GBfits in fast memory~54 tok/sollama run gemma4:31b-it-q4_K_M
M4 Pro 48GBOllamaQ4_K_M22.5 GBfits in fast memory~11 tok/sollama run gemma4:31b-it-q4_K_M
Mac Studio M4 Max (40c GPU) 48GBOllamaQ4_K_M22.5 GBfits in fast memory~22 tok/sollama run gemma4:31b-it-q4_K_M
Mac Studio M5 Max (40c GPU) 48GBOllamaQ4_K_M22.5 GBfits in fast memory~25 tok/sollama run gemma4:31b-it-q4_K_M
M1 Max 64GBOllamaQ8_036.5 GBfits in fast memory~9 tok/sollama run gemma4:31b-it-q8_0
M2 Max 64GBOllamaQ8_036.5 GBfits in fast memory~9 tok/sollama run gemma4:31b-it-q8_0
M3 Max 64GBOllamaQ8_036.5 GBfits in fast memory~9 tok/sollama run gemma4:31b-it-q8_0
M4 Max 64GBOllamaQ8_036.5 GBfits in fast memory~13 tok/sollama run gemma4:31b-it-q8_0
Mac Studio M4 Max (40c GPU) 64GBOllamaQ8_036.5 GBfits in fast memory~13 tok/sollama run gemma4:31b-it-q8_0
Mac Studio M5 Max (40c GPU) 64GBOllamaQ8_036.5 GBfits in fast memory~14 tok/sollama run gemma4:31b-it-q8_0
DGX Spark 64GB (ASUS, Dell, HP, MSI, Acer, Gigabyte)OllamaQ8_036.5 GBfits in fast memory~6 tok/sollama run gemma4:31b-it-q8_0
Mac Studio M3 Ultra 96GBOllamaQ8_036.5 GBfits in fast memory~19 tok/sollama run gemma4:31b-it-q8_0
Mac Studio M5 Ultra 96GBOllamaQ8_036.5 GBfits in fast memory~28 tok/sollama run gemma4:31b-it-q8_0
M3 Max 128GBOllamaQ8_036.5 GBfits in fast memory~9 tok/sollama run gemma4:31b-it-q8_0
M4 Max 128GBOllamaQ8_036.5 GBfits in fast memory~13 tok/sollama run gemma4:31b-it-q8_0
Mac Studio M4 Max (40c GPU) 128GBOllamaQ8_036.5 GBfits in fast memory~13 tok/sollama run gemma4:31b-it-q8_0
Mac Studio M5 Max (40c GPU) 128GBOllamaQ8_036.5 GBfits in fast memory~14 tok/sollama run gemma4:31b-it-q8_0
DGX Spark 128GB (NVIDIA, ASUS, Dell, Lenovo, HP, MSI, Acer, Gigabyte)OllamaQ8_036.5 GBfits in fast memory~6 tok/sollama run gemma4:31b-it-q8_0
M2 Ultra 192GBOllamaQ8_036.5 GBfits in fast memory~19 tok/sollama run gemma4:31b-it-q8_0
2x Mac Studio M5 Max (40c GPU) 128GBllama.cppQ8_0 GGUF35.7 GBfits in fast memory~13 tok/sllama-server -hf unsloth/gemma-4-31B-it-GGUF:Q8_0 --rpc node2:50052 -c 8192 # run rpc-server on each other node
Mac Studio M3 Ultra 256GBOllamaQ8_036.5 GBfits in fast memory~19 tok/sollama run gemma4:31b-it-q8_0
Mac Studio M5 Ultra (64c GPU) 256GBOllamaQ8_036.5 GBfits in fast memory~28 tok/sollama run gemma4:31b-it-q8_0
Mac Studio M5 Ultra (80c GPU) 256GBOllamaQ8_036.5 GBfits in fast memory~28 tok/sollama run gemma4:31b-it-q8_0
2x DGX Spark 128GBllama.cppQ8_0 GGUF35.7 GBfits in fast memory~5 tok/sllama-server -hf unsloth/gemma-4-31B-it-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 GGUF35.7 GBfits in fast memory~11 tok/sllama-server -hf unsloth/gemma-4-31B-it-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 GGUF35.7 GBfits in fast memory~25 tok/sllama-server -hf unsloth/gemma-4-31B-it-GGUF:Q8_0 --rpc node2:50052 -c 8192 # run rpc-server on each other node
Mac Studio M3 Ultra (80c GPU) 512GBOllamaQ8_036.5 GBfits in fast memory~19 tok/sollama run gemma4:31b-it-q8_0
4x DGX Spark 128GBllama.cppQ8_0 GGUF35.7 GBfits in fast memory~5 tok/sllama-server -hf unsloth/gemma-4-31B-it-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 GGUF35.7 GBfits in fast memory~22 tok/sllama-server -hf unsloth/gemma-4-31B-it-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