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Can I run Gemma 3 4B locally?

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Ollama weight files: Q4_K_M 3.4 GB (gemma3:4b); Q8_0 5 GB (gemma3:4b-it-q8_0).

Yes on 62 machines in this list. The smallest is M1 8GB: Q4_K_M, about 4.2 GB, roughly 16 tokens per second, via Ollama. ollama run gemma3:4b

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

Open Gemma 3 4B in the checker

Hardware that fits

HardwareRuntimeQuantMemoryFitSpeedCommand
M1 8GBOllamaQ4_K_M4.2 GBfits in fast memory~16 tok/sollama run gemma3:4b
M2 8GBOllamaQ4_K_M4.2 GBfits in fast memory~24 tok/sollama run gemma3:4b
M3 8GBOllamaQ4_K_M4.2 GBfits in fast memory~24 tok/sollama run gemma3:4b
RTX 3060 Ti 8GBOllamaQ8_05.8 GBfits in fast memory~54 tok/sollama run gemma3:4b-it-q8_0
RTX 3070 8GBOllamaQ8_05.8 GBfits in fast memory~54 tok/sollama run gemma3:4b-it-q8_0
RTX 4060 8GBOllamaQ8_05.8 GBfits in fast memory~33 tok/sollama run gemma3:4b-it-q8_0
RX 7600 8GBOllamaQ8_05.8 GBfits in fast memory~35 tok/sollama run gemma3:4b-it-q8_0
RTX 3080 10GBOllamaQ8_05.8 GBfits in fast memory~91 tok/sollama run gemma3:4b-it-q8_0
M1 16GBOllamaQ8_05.8 GBfits in fast memory~11 tok/sollama run gemma3:4b-it-q8_0
M2 16GBOllamaQ8_05.8 GBfits in fast memory~16 tok/sollama run gemma3:4b-it-q8_0
M3 16GBOllamaQ8_05.8 GBfits in fast memory~16 tok/sollama run gemma3:4b-it-q8_0
M4 16GBOllamaQ8_05.8 GBfits in fast memory~19 tok/sollama run gemma3:4b-it-q8_0
RTX 3060 12GBOllamaQ8_05.8 GBfits in fast memory~43 tok/sollama run gemma3:4b-it-q8_0
RTX 4070 12GBOllamaQ8_05.8 GBfits in fast memory~60 tok/sollama run gemma3:4b-it-q8_0
RTX 5070 12GBOllamaQ8_05.8 GBfits in fast memory~81 tok/sollama run gemma3:4b-it-q8_0
RTX 4060 Ti 16GBOllamaQ8_05.8 GBfits in fast memory~35 tok/sollama run gemma3:4b-it-q8_0
RTX 4070 Ti Super 16GBOllamaQ8_05.8 GBfits in fast memory~81 tok/sollama run gemma3:4b-it-q8_0
RTX 4080 16GBOllamaQ8_05.8 GBfits in fast memory~86 tok/sollama run gemma3:4b-it-q8_0
RTX 5080 16GBOllamaQ8_05.8 GBfits in fast memory~115 tok/sollama run gemma3:4b-it-q8_0
RX 7800 XT 16GBOllamaQ8_05.8 GBfits in fast memory~75 tok/sollama run gemma3:4b-it-q8_0
RX 9070 XT 16GBOllamaQ8_05.8 GBfits in fast memory~77 tok/sollama run gemma3:4b-it-q8_0
M2 24GBOllamaQ8_05.8 GBfits in fast memory~16 tok/sollama run gemma3:4b-it-q8_0
M3 24GBOllamaQ8_05.8 GBfits in fast memory~16 tok/sollama run gemma3:4b-it-q8_0
M4 24GBOllamaQ8_05.8 GBfits in fast memory~19 tok/sollama run gemma3:4b-it-q8_0
RTX 3090 24GBOllamaQ8_05.8 GBfits in fast memory~112 tok/sollama run gemma3:4b-it-q8_0
RTX 4090 24GBOllamaQ8_05.8 GBfits in fast memory~121 tok/sollama run gemma3:4b-it-q8_0
RX 7900 XTX 24GBOllamaQ8_05.8 GBfits in fast memory~115 tok/sollama run gemma3:4b-it-q8_0
M1 Pro 32GBOllamaQ8_05.8 GBfits in fast memory~32 tok/sollama run gemma3:4b-it-q8_0
M2 Pro 32GBOllamaQ8_05.8 GBfits in fast memory~32 tok/sollama run gemma3:4b-it-q8_0
M4 32GBOllamaQ8_05.8 GBfits in fast memory~19 tok/sollama run gemma3:4b-it-q8_0
M3 Pro 36GBOllamaQ8_05.8 GBfits in fast memory~24 tok/sollama run gemma3:4b-it-q8_0
Mac Studio M4 Max (32c GPU) 36GBOllamaQ8_05.8 GBfits in fast memory~66 tok/sollama run gemma3:4b-it-q8_0
Mac Studio M5 Max (32c GPU) 36GBOllamaQ8_05.8 GBfits in fast memory~74 tok/sollama run gemma3:4b-it-q8_0
RTX 5090 32GBOllamaQ8_05.8 GBfits in fast memory~215 tok/sollama run gemma3:4b-it-q8_0
M4 Pro 48GBOllamaQ8_05.8 GBfits in fast memory~44 tok/sollama run gemma3:4b-it-q8_0
Mac Studio M4 Max (40c GPU) 48GBOllamaQ8_05.8 GBfits in fast memory~87 tok/sollama run gemma3:4b-it-q8_0
Mac Studio M5 Max (40c GPU) 48GBOllamaQ8_05.8 GBfits in fast memory~98 tok/sollama run gemma3:4b-it-q8_0
M1 Max 64GBOllamaQ8_05.8 GBfits in fast memory~64 tok/sollama run gemma3:4b-it-q8_0
M2 Max 64GBOllamaQ8_05.8 GBfits in fast memory~64 tok/sollama run gemma3:4b-it-q8_0
M3 Max 64GBOllamaQ8_05.8 GBfits in fast memory~64 tok/sollama run gemma3:4b-it-q8_0
M4 Max 64GBOllamaQ8_05.8 GBfits in fast memory~87 tok/sollama run gemma3:4b-it-q8_0
Mac Studio M4 Max (40c GPU) 64GBOllamaQ8_05.8 GBfits in fast memory~87 tok/sollama run gemma3:4b-it-q8_0
Mac Studio M5 Max (40c GPU) 64GBOllamaQ8_05.8 GBfits in fast memory~98 tok/sollama run gemma3:4b-it-q8_0
DGX Spark 64GB (ASUS, Dell, HP, MSI, Acer, Gigabyte)OllamaQ8_05.8 GBfits in fast memory~41 tok/sollama run gemma3:4b-it-q8_0
Mac Studio M3 Ultra 96GBOllamaQ8_05.8 GBfits in fast memory~131 tok/sollama run gemma3:4b-it-q8_0
Mac Studio M5 Ultra 96GBOllamaQ8_05.8 GBfits in fast memory~192 tok/sollama run gemma3:4b-it-q8_0
M3 Max 128GBOllamaQ8_05.8 GBfits in fast memory~64 tok/sollama run gemma3:4b-it-q8_0
M4 Max 128GBOllamaQ8_05.8 GBfits in fast memory~87 tok/sollama run gemma3:4b-it-q8_0
Mac Studio M4 Max (40c GPU) 128GBOllamaQ8_05.8 GBfits in fast memory~87 tok/sollama run gemma3:4b-it-q8_0
Mac Studio M5 Max (40c GPU) 128GBOllamaQ8_05.8 GBfits in fast memory~98 tok/sollama run gemma3:4b-it-q8_0
DGX Spark 128GB (NVIDIA, ASUS, Dell, Lenovo, HP, MSI, Acer, Gigabyte)OllamaQ8_05.8 GBfits in fast memory~41 tok/sollama run gemma3:4b-it-q8_0
M2 Ultra 192GBOllamaQ8_05.8 GBfits in fast memory~128 tok/sollama run gemma3:4b-it-q8_0
2x Mac Studio M5 Max (40c GPU) 128GBllama.cppQ8_0 GGUF4.9 GBfits in fast memory~101 tok/sllama-server -hf unsloth/gemma-3-4b-it-GGUF:Q8_0 --rpc node2:50052 -c 8192 # run rpc-server on each other node
Mac Studio M3 Ultra 256GBOllamaQ8_05.8 GBfits in fast memory~131 tok/sollama run gemma3:4b-it-q8_0
Mac Studio M5 Ultra (64c GPU) 256GBOllamaQ8_05.8 GBfits in fast memory~192 tok/sollama run gemma3:4b-it-q8_0
Mac Studio M5 Ultra (80c GPU) 256GBOllamaQ8_05.8 GBfits in fast memory~192 tok/sollama run gemma3:4b-it-q8_0
2x DGX Spark 128GBllama.cppQ8_0 GGUF4.9 GBfits in fast memory~42 tok/sllama-server -hf unsloth/gemma-3-4b-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 GGUF4.9 GBfits in fast memory~89 tok/sllama-server -hf unsloth/gemma-3-4b-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 GGUF4.9 GBfits in fast memory~198 tok/sllama-server -hf unsloth/gemma-3-4b-it-GGUF:Q8_0 --rpc node2:50052 -c 8192 # run rpc-server on each other node
Mac Studio M3 Ultra (80c GPU) 512GBOllamaQ8_05.8 GBfits in fast memory~131 tok/sollama run gemma3:4b-it-q8_0
4x DGX Spark 128GBllama.cppQ8_0 GGUF4.9 GBfits in fast memory~37 tok/sllama-server -hf unsloth/gemma-3-4b-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 GGUF4.9 GBfits in fast memory~174 tok/sllama-server -hf unsloth/gemma-3-4b-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 2026-10-16.

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