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Can I run Gemma 3 12B locally?

Google · 12.2B parameters · chat, vision.

Ollama weight files: Q4_K_M 8.2 GB (gemma3:12b); Q8_0 13 GB (gemma3:12b-it-q8_0).

Yes on 59 machines in this list. The smallest is RTX 3060 Ti 8GB: Q4_K_M, about 9.4 GB, roughly 15 tokens per second, via Ollama. ollama run gemma3:12b

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

Open Gemma 3 12B in the checker

Hardware that fits

HardwareRuntimeQuantMemoryFitSpeedCommand
RTX 3060 Ti 8GBOllamaQ4_K_M9.4 GBpartial offload (slower)~15 tok/sollama run gemma3:12b
RTX 3070 8GBOllamaQ4_K_M9.4 GBpartial offload (slower)~15 tok/sollama run gemma3:12b
RTX 4060 8GBOllamaQ4_K_M9.4 GBpartial offload (slower)~12 tok/sollama run gemma3:12b
RX 7600 8GBOllamaQ4_K_M9.4 GBpartial offload (slower)~13 tok/sollama run gemma3:12b
RTX 3080 10GBOllamaQ4_K_M9.4 GBfits in fast memory~56 tok/sollama run gemma3:12b
M1 16GBOllamaQ4_K_M9.4 GBfits in fast memory~7 tok/sollama run gemma3:12b
M2 16GBOllamaQ4_K_M9.4 GBfits in fast memory~10 tok/sollama run gemma3:12b
M3 16GBOllamaQ4_K_M9.4 GBfits in fast memory~10 tok/sollama run gemma3:12b
M4 16GBOllamaQ4_K_M9.4 GBfits in fast memory~12 tok/sollama run gemma3:12b
RTX 3060 12GBOllamaQ4_K_M9.4 GBfits in fast memory~26 tok/sollama run gemma3:12b
RTX 4070 12GBOllamaQ4_K_M9.4 GBfits in fast memory~37 tok/sollama run gemma3:12b
RTX 5070 12GBOllamaQ4_K_M9.4 GBfits in fast memory~49 tok/sollama run gemma3:12b
RTX 4060 Ti 16GBOllamaQ8_014.2 GBfits in fast memory~13 tok/sollama run gemma3:12b-it-q8_0
RTX 4070 Ti Super 16GBOllamaQ8_014.2 GBfits in fast memory~31 tok/sollama run gemma3:12b-it-q8_0
RTX 4080 16GBOllamaQ8_014.2 GBfits in fast memory~33 tok/sollama run gemma3:12b-it-q8_0
RTX 5080 16GBOllamaQ8_014.2 GBfits in fast memory~44 tok/sollama run gemma3:12b-it-q8_0
RX 7800 XT 16GBOllamaQ8_014.2 GBfits in fast memory~29 tok/sollama run gemma3:12b-it-q8_0
RX 9070 XT 16GBOllamaQ8_014.2 GBfits in fast memory~30 tok/sollama run gemma3:12b-it-q8_0
M2 24GBOllamaQ8_014.2 GBfits in fast memory~6 tok/sollama run gemma3:12b-it-q8_0
M3 24GBOllamaQ8_014.2 GBfits in fast memory~6 tok/sollama run gemma3:12b-it-q8_0
M4 24GBOllamaQ8_014.2 GBfits in fast memory~7 tok/sollama run gemma3:12b-it-q8_0
RTX 3090 24GBOllamaQ8_014.2 GBfits in fast memory~43 tok/sollama run gemma3:12b-it-q8_0
RTX 4090 24GBOllamaQ8_014.2 GBfits in fast memory~47 tok/sollama run gemma3:12b-it-q8_0
RX 7900 XTX 24GBOllamaQ8_014.2 GBfits in fast memory~44 tok/sollama run gemma3:12b-it-q8_0
M1 Pro 32GBOllamaQ8_014.2 GBfits in fast memory~12 tok/sollama run gemma3:12b-it-q8_0
M2 Pro 32GBOllamaQ8_014.2 GBfits in fast memory~12 tok/sollama run gemma3:12b-it-q8_0
M4 32GBOllamaQ8_014.2 GBfits in fast memory~7 tok/sollama run gemma3:12b-it-q8_0
M3 Pro 36GBOllamaQ8_014.2 GBfits in fast memory~9 tok/sollama run gemma3:12b-it-q8_0
Mac Studio M4 Max (32c GPU) 36GBOllamaQ8_014.2 GBfits in fast memory~25 tok/sollama run gemma3:12b-it-q8_0
Mac Studio M5 Max (32c GPU) 36GBOllamaQ8_014.2 GBfits in fast memory~28 tok/sollama run gemma3:12b-it-q8_0
RTX 5090 32GBOllamaQ8_014.2 GBfits in fast memory~83 tok/sollama run gemma3:12b-it-q8_0
M4 Pro 48GBOllamaQ8_014.2 GBfits in fast memory~17 tok/sollama run gemma3:12b-it-q8_0
Mac Studio M4 Max (40c GPU) 48GBOllamaQ8_014.2 GBfits in fast memory~34 tok/sollama run gemma3:12b-it-q8_0
Mac Studio M5 Max (40c GPU) 48GBOllamaQ8_014.2 GBfits in fast memory~38 tok/sollama run gemma3:12b-it-q8_0
M1 Max 64GBOllamaQ8_014.2 GBfits in fast memory~25 tok/sollama run gemma3:12b-it-q8_0
M2 Max 64GBOllamaQ8_014.2 GBfits in fast memory~25 tok/sollama run gemma3:12b-it-q8_0
M3 Max 64GBOllamaQ8_014.2 GBfits in fast memory~25 tok/sollama run gemma3:12b-it-q8_0
M4 Max 64GBOllamaQ8_014.2 GBfits in fast memory~34 tok/sollama run gemma3:12b-it-q8_0
Mac Studio M4 Max (40c GPU) 64GBOllamaQ8_014.2 GBfits in fast memory~34 tok/sollama run gemma3:12b-it-q8_0
Mac Studio M5 Max (40c GPU) 64GBOllamaQ8_014.2 GBfits in fast memory~38 tok/sollama run gemma3:12b-it-q8_0
DGX Spark 64GB (ASUS, Dell, HP, MSI, Acer, Gigabyte)OllamaQ8_014.2 GBfits in fast memory~16 tok/sollama run gemma3:12b-it-q8_0
Mac Studio M3 Ultra 96GBOllamaQ8_014.2 GBfits in fast memory~50 tok/sollama run gemma3:12b-it-q8_0
Mac Studio M5 Ultra 96GBOllamaQ8_014.2 GBfits in fast memory~74 tok/sollama run gemma3:12b-it-q8_0
M3 Max 128GBOllamaQ8_014.2 GBfits in fast memory~25 tok/sollama run gemma3:12b-it-q8_0
M4 Max 128GBOllamaQ8_014.2 GBfits in fast memory~34 tok/sollama run gemma3:12b-it-q8_0
Mac Studio M4 Max (40c GPU) 128GBOllamaQ8_014.2 GBfits in fast memory~34 tok/sollama run gemma3:12b-it-q8_0
Mac Studio M5 Max (40c GPU) 128GBOllamaQ8_014.2 GBfits in fast memory~38 tok/sollama run gemma3:12b-it-q8_0
DGX Spark 128GB (NVIDIA, ASUS, Dell, Lenovo, HP, MSI, Acer, Gigabyte)OllamaQ8_014.2 GBfits in fast memory~16 tok/sollama run gemma3:12b-it-q8_0
M2 Ultra 192GBOllamaQ8_014.2 GBfits in fast memory~49 tok/sollama run gemma3:12b-it-q8_0
2x Mac Studio M5 Max (40c GPU) 128GBllama.cppQ8_0 GGUF13.7 GBfits in fast memory~33 tok/sllama-server -hf unsloth/gemma-3-12b-it-GGUF:Q8_0 --rpc node2:50052 -c 8192 # run rpc-server on each other node
Mac Studio M3 Ultra 256GBOllamaQ8_014.2 GBfits in fast memory~50 tok/sollama run gemma3:12b-it-q8_0
Mac Studio M5 Ultra (64c GPU) 256GBOllamaQ8_014.2 GBfits in fast memory~74 tok/sollama run gemma3:12b-it-q8_0
Mac Studio M5 Ultra (80c GPU) 256GBOllamaQ8_014.2 GBfits in fast memory~74 tok/sollama run gemma3:12b-it-q8_0
2x DGX Spark 128GBllama.cppQ8_0 GGUF13.7 GBfits in fast memory~14 tok/sllama-server -hf unsloth/gemma-3-12b-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 GGUF13.7 GBfits in fast memory~29 tok/sllama-server -hf unsloth/gemma-3-12b-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 GGUF13.7 GBfits in fast memory~65 tok/sllama-server -hf unsloth/gemma-3-12b-it-GGUF:Q8_0 --rpc node2:50052 -c 8192 # run rpc-server on each other node
Mac Studio M3 Ultra (80c GPU) 512GBOllamaQ8_014.2 GBfits in fast memory~50 tok/sollama run gemma3:12b-it-q8_0
4x DGX Spark 128GBllama.cppQ8_0 GGUF13.7 GBfits in fast memory~12 tok/sllama-server -hf unsloth/gemma-3-12b-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 GGUF13.7 GBfits in fast memory~58 tok/sllama-server -hf unsloth/gemma-3-12b-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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