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Can I run North Mini Code 1.0 30B (MoE) locally?

Cohere · 30.5B parameters · coding, reasoning.

Ollama weight files: Q4_K_M 19 GB (north-mini-code-1.0:latest); Q8_0 32 GB (north-mini-code-1.0:q8_0).

Yes on 47 machines in this list. The smallest is RTX 3060 12GB: Q4_K_M, about 21.1 GB, roughly 4 tokens per second, via Ollama. ollama run north-mini-code-1.0:latest

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

Open North Mini Code 1.0 30B (MoE) in the checker

Hardware that fits

HardwareRuntimeQuantMemoryFitSpeedCommand
RTX 3060 12GBOllamaQ4_K_M21.1 GBpartial offload (slower)~4 tok/sollama run north-mini-code-1.0:latest
RTX 4070 12GBOllamaQ4_K_M21.1 GBpartial offload (slower)~4 tok/sollama run north-mini-code-1.0:latest
RTX 5070 12GBOllamaQ4_K_M21.1 GBpartial offload (slower)~4 tok/sollama run north-mini-code-1.0:latest
RTX 4060 Ti 16GBOllamaQ4_K_M21.1 GBpartial offload (slower)~5 tok/sollama run north-mini-code-1.0:latest
RTX 4070 Ti Super 16GBOllamaQ4_K_M21.1 GBpartial offload (slower)~6 tok/sollama run north-mini-code-1.0:latest
RTX 4080 16GBOllamaQ4_K_M21.1 GBpartial offload (slower)~6 tok/sollama run north-mini-code-1.0:latest
RTX 5080 16GBOllamaQ4_K_M21.1 GBpartial offload (slower)~7 tok/sollama run north-mini-code-1.0:latest
RX 7800 XT 16GBOllamaQ4_K_M21.1 GBpartial offload (slower)~6 tok/sollama run north-mini-code-1.0:latest
RX 9070 XT 16GBOllamaQ4_K_M21.1 GBpartial offload (slower)~6 tok/sollama run north-mini-code-1.0:latest
RTX 3090 24GBOllamaQ4_K_M21.1 GBfits in fast memory~30 tok/sollama run north-mini-code-1.0:latest
RTX 4090 24GBOllamaQ4_K_M21.1 GBfits in fast memory~32 tok/sollama run north-mini-code-1.0:latest
RX 7900 XTX 24GBOllamaQ4_K_M21.1 GBfits in fast memory~30 tok/sollama run north-mini-code-1.0:latest
M1 Pro 32GBOllamaQ4_K_M21.1 GBfits in fast memory~8 tok/sollama run north-mini-code-1.0:latest
M2 Pro 32GBOllamaQ4_K_M21.1 GBfits in fast memory~8 tok/sollama run north-mini-code-1.0:latest
M4 32GBOllamaQ4_K_M21.1 GBfits in fast memory~5 tok/sollama run north-mini-code-1.0:latest
M3 Pro 36GBOllamaQ4_K_M21.1 GBfits in fast memory~6 tok/sollama run north-mini-code-1.0:latest
Mac Studio M4 Max (32c GPU) 36GBOllamaQ4_K_M21.1 GBfits in fast memory~17 tok/sollama run north-mini-code-1.0:latest
Mac Studio M5 Max (32c GPU) 36GBOllamaQ4_K_M21.1 GBfits in fast memory~19 tok/sollama run north-mini-code-1.0:latest
RTX 5090 32GBOllamaQ4_K_M21.1 GBfits in fast memory~57 tok/sollama run north-mini-code-1.0:latest
M4 Pro 48GBOllamaQ8_034.1 GBfits in fast memory~7 tok/sollama run north-mini-code-1.0:q8_0
Mac Studio M4 Max (40c GPU) 48GBOllamaQ8_034.1 GBfits in fast memory~14 tok/sollama run north-mini-code-1.0:q8_0
Mac Studio M5 Max (40c GPU) 48GBOllamaQ8_034.1 GBfits in fast memory~15 tok/sollama run north-mini-code-1.0:q8_0
M1 Max 64GBOllamaQ8_034.1 GBfits in fast memory~10 tok/sollama run north-mini-code-1.0:q8_0
M2 Max 64GBOllamaQ8_034.1 GBfits in fast memory~10 tok/sollama run north-mini-code-1.0:q8_0
M3 Max 64GBOllamaQ8_034.1 GBfits in fast memory~10 tok/sollama run north-mini-code-1.0:q8_0
M4 Max 64GBOllamaQ8_034.1 GBfits in fast memory~14 tok/sollama run north-mini-code-1.0:q8_0
Mac Studio M4 Max (40c GPU) 64GBOllamaQ8_034.1 GBfits in fast memory~14 tok/sollama run north-mini-code-1.0:q8_0
Mac Studio M5 Max (40c GPU) 64GBOllamaQ8_034.1 GBfits in fast memory~15 tok/sollama run north-mini-code-1.0:q8_0
DGX Spark 64GB (ASUS, Dell, HP, MSI, Acer, Gigabyte)OllamaQ8_034.1 GBfits in fast memory~6 tok/sollama run north-mini-code-1.0:q8_0
Mac Studio M3 Ultra 96GBOllamaQ8_034.1 GBfits in fast memory~20 tok/sollama run north-mini-code-1.0:q8_0
Mac Studio M5 Ultra 96GBOllamaQ8_034.1 GBfits in fast memory~30 tok/sollama run north-mini-code-1.0:q8_0
M3 Max 128GBOllamaQ8_034.1 GBfits in fast memory~10 tok/sollama run north-mini-code-1.0:q8_0
M4 Max 128GBOllamaQ8_034.1 GBfits in fast memory~14 tok/sollama run north-mini-code-1.0:q8_0
Mac Studio M4 Max (40c GPU) 128GBOllamaQ8_034.1 GBfits in fast memory~14 tok/sollama run north-mini-code-1.0:q8_0
Mac Studio M5 Max (40c GPU) 128GBOllamaQ8_034.1 GBfits in fast memory~15 tok/sollama run north-mini-code-1.0:q8_0
DGX Spark 128GB (NVIDIA, ASUS, Dell, Lenovo, HP, MSI, Acer, Gigabyte)OllamaQ8_034.1 GBfits in fast memory~6 tok/sollama run north-mini-code-1.0:q8_0
M2 Ultra 192GBOllamaQ8_034.1 GBfits in fast memory~20 tok/sollama run north-mini-code-1.0:q8_0
2x Mac Studio M5 Max (40c GPU) 128GBllama.cppQ8_0 GGUF34.6 GBfits in fast memory~13 tok/sllama-server -hf unsloth/North-Mini-Code-1.0-GGUF:Q8_0 --rpc node2:50052 -c 8192 # run rpc-server on each other node
Mac Studio M3 Ultra 256GBOllamaQ8_034.1 GBfits in fast memory~20 tok/sollama run north-mini-code-1.0:q8_0
Mac Studio M5 Ultra (64c GPU) 256GBOllamaQ8_034.1 GBfits in fast memory~30 tok/sollama run north-mini-code-1.0:q8_0
Mac Studio M5 Ultra (80c GPU) 256GBOllamaQ8_034.1 GBfits in fast memory~30 tok/sollama run north-mini-code-1.0:q8_0
2x DGX Spark 128GBllama.cppQ8_0 GGUF34.6 GBfits in fast memory~5 tok/sllama-server -hf unsloth/North-Mini-Code-1.0-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 GGUF34.6 GBfits in fast memory~11 tok/sllama-server -hf unsloth/North-Mini-Code-1.0-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 GGUF34.6 GBfits in fast memory~25 tok/sllama-server -hf unsloth/North-Mini-Code-1.0-GGUF:Q8_0 --rpc node2:50052 -c 8192 # run rpc-server on each other node
Mac Studio M3 Ultra (80c GPU) 512GBOllamaQ8_034.1 GBfits in fast memory~20 tok/sollama run north-mini-code-1.0:q8_0
4x DGX Spark 128GBllama.cppQ8_0 GGUF34.6 GBfits in fast memory~5 tok/sllama-server -hf unsloth/North-Mini-Code-1.0-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 GGUF34.6 GBfits in fast memory~22 tok/sllama-server -hf unsloth/North-Mini-Code-1.0-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