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Can I run Nemotron Labs Dory 1.0 4B locally?

NVIDIA · 3.98B parameters · chat.

Ollama weight files: Q5_K_M 3.67 GB (hf.co/nvidia/NVIDIA-Nemotron-Labs-Dory1.0-4B-GGUF:Q5_K_M, size from the Hugging Face file listing).

Yes on 85 machines in this list. The smallest is M1 8GB: Q5_K_M, about 4.5 GB, roughly 15 tokens per second, via Ollama. ollama run hf.co/nvidia/NVIDIA-Nemotron-Labs-Dory1.0-4B-GGUF:Q5_K_M

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

Open Nemotron Labs Dory 1.0 4B in the checker

Hardware that fits

HardwareRuntimeQuantMemoryFitSpeedCommand
M1 8GBOllamaQ5_K_M4.5 GBfits in fast memory~15 tok/sollama run hf.co/nvidia/NVIDIA-Nemotron-Labs-Dory1.0-4B-GGUF:Q5_K_M
M2 8GBOllamaQ5_K_M4.5 GBfits in fast memory~22 tok/sollama run hf.co/nvidia/NVIDIA-Nemotron-Labs-Dory1.0-4B-GGUF:Q5_K_M
M3 8GBOllamaQ5_K_M4.5 GBfits in fast memory~22 tok/sollama run hf.co/nvidia/NVIDIA-Nemotron-Labs-Dory1.0-4B-GGUF:Q5_K_M
RTX 3060 8GBOllamaQ5_K_M4.5 GBfits in fast memory~39 tok/sollama run hf.co/nvidia/NVIDIA-Nemotron-Labs-Dory1.0-4B-GGUF:Q5_K_M
RTX 3060 Ti 8GBOllamaQ5_K_M4.5 GBfits in fast memory~73 tok/sollama run hf.co/nvidia/NVIDIA-Nemotron-Labs-Dory1.0-4B-GGUF:Q5_K_M
RTX 3070 8GBOllamaQ5_K_M4.5 GBfits in fast memory~73 tok/sollama run hf.co/nvidia/NVIDIA-Nemotron-Labs-Dory1.0-4B-GGUF:Q5_K_M
RTX 4060 8GBOllamaQ5_K_M4.5 GBfits in fast memory~44 tok/sollama run hf.co/nvidia/NVIDIA-Nemotron-Labs-Dory1.0-4B-GGUF:Q5_K_M
RTX 4060 Ti 8GBOllamaQ5_K_M4.5 GBfits in fast memory~47 tok/sollama run hf.co/nvidia/NVIDIA-Nemotron-Labs-Dory1.0-4B-GGUF:Q5_K_M
RX 7600 8GBOllamaQ5_K_M4.5 GBfits in fast memory~47 tok/sollama run hf.co/nvidia/NVIDIA-Nemotron-Labs-Dory1.0-4B-GGUF:Q5_K_M
RTX 3080 10GBOllamaQ5_K_M4.5 GBfits in fast memory~124 tok/sollama run hf.co/nvidia/NVIDIA-Nemotron-Labs-Dory1.0-4B-GGUF:Q5_K_M
M1 16GBOllamaQ5_K_M4.5 GBfits in fast memory~15 tok/sollama run hf.co/nvidia/NVIDIA-Nemotron-Labs-Dory1.0-4B-GGUF:Q5_K_M
M1 Pro 16GBOllamaQ5_K_M4.5 GBfits in fast memory~44 tok/sollama run hf.co/nvidia/NVIDIA-Nemotron-Labs-Dory1.0-4B-GGUF:Q5_K_M
M2 16GBOllamaQ5_K_M4.5 GBfits in fast memory~22 tok/sollama run hf.co/nvidia/NVIDIA-Nemotron-Labs-Dory1.0-4B-GGUF:Q5_K_M
M2 Pro 16GBOllamaQ5_K_M4.5 GBfits in fast memory~44 tok/sollama run hf.co/nvidia/NVIDIA-Nemotron-Labs-Dory1.0-4B-GGUF:Q5_K_M
M3 16GBOllamaQ5_K_M4.5 GBfits in fast memory~22 tok/sollama run hf.co/nvidia/NVIDIA-Nemotron-Labs-Dory1.0-4B-GGUF:Q5_K_M
M4 16GBOllamaQ5_K_M4.5 GBfits in fast memory~26 tok/sollama run hf.co/nvidia/NVIDIA-Nemotron-Labs-Dory1.0-4B-GGUF:Q5_K_M
RTX 3060 12GBOllamaQ5_K_M4.5 GBfits in fast memory~59 tok/sollama run hf.co/nvidia/NVIDIA-Nemotron-Labs-Dory1.0-4B-GGUF:Q5_K_M
RTX 3080 12GBOllamaQ5_K_M4.5 GBfits in fast memory~149 tok/sollama run hf.co/nvidia/NVIDIA-Nemotron-Labs-Dory1.0-4B-GGUF:Q5_K_M
RTX 4070 12GBOllamaQ5_K_M4.5 GBfits in fast memory~82 tok/sollama run hf.co/nvidia/NVIDIA-Nemotron-Labs-Dory1.0-4B-GGUF:Q5_K_M
RTX 5070 12GBOllamaQ5_K_M4.5 GBfits in fast memory~110 tok/sollama run hf.co/nvidia/NVIDIA-Nemotron-Labs-Dory1.0-4B-GGUF:Q5_K_M
M3 Pro 18GBOllamaQ5_K_M4.5 GBfits in fast memory~33 tok/sollama run hf.co/nvidia/NVIDIA-Nemotron-Labs-Dory1.0-4B-GGUF:Q5_K_M
RTX 4060 Ti 16GBOllamaQ5_K_M4.5 GBfits in fast memory~47 tok/sollama run hf.co/nvidia/NVIDIA-Nemotron-Labs-Dory1.0-4B-GGUF:Q5_K_M
RTX 4070 Ti Super 16GBOllamaQ5_K_M4.5 GBfits in fast memory~110 tok/sollama run hf.co/nvidia/NVIDIA-Nemotron-Labs-Dory1.0-4B-GGUF:Q5_K_M
RTX 4080 16GBOllamaQ5_K_M4.5 GBfits in fast memory~117 tok/sollama run hf.co/nvidia/NVIDIA-Nemotron-Labs-Dory1.0-4B-GGUF:Q5_K_M
RTX 5080 16GBOllamaQ5_K_M4.5 GBfits in fast memory~157 tok/sollama run hf.co/nvidia/NVIDIA-Nemotron-Labs-Dory1.0-4B-GGUF:Q5_K_M
RX 7800 XT 16GBOllamaQ5_K_M4.5 GBfits in fast memory~102 tok/sollama run hf.co/nvidia/NVIDIA-Nemotron-Labs-Dory1.0-4B-GGUF:Q5_K_M
RX 9070 XT 16GBOllamaQ5_K_M4.5 GBfits in fast memory~105 tok/sollama run hf.co/nvidia/NVIDIA-Nemotron-Labs-Dory1.0-4B-GGUF:Q5_K_M
M2 24GBOllamaQ5_K_M4.5 GBfits in fast memory~22 tok/sollama run hf.co/nvidia/NVIDIA-Nemotron-Labs-Dory1.0-4B-GGUF:Q5_K_M
M3 24GBOllamaQ5_K_M4.5 GBfits in fast memory~22 tok/sollama run hf.co/nvidia/NVIDIA-Nemotron-Labs-Dory1.0-4B-GGUF:Q5_K_M
M4 24GBOllamaQ5_K_M4.5 GBfits in fast memory~26 tok/sollama run hf.co/nvidia/NVIDIA-Nemotron-Labs-Dory1.0-4B-GGUF:Q5_K_M
M4 Pro 24GBOllamaQ5_K_M4.5 GBfits in fast memory~60 tok/sollama run hf.co/nvidia/NVIDIA-Nemotron-Labs-Dory1.0-4B-GGUF:Q5_K_M
RTX 3090 24GBOllamaQ5_K_M4.5 GBfits in fast memory~153 tok/sollama run hf.co/nvidia/NVIDIA-Nemotron-Labs-Dory1.0-4B-GGUF:Q5_K_M
RTX 4090 24GBOllamaQ5_K_M4.5 GBfits in fast memory~165 tok/sollama run hf.co/nvidia/NVIDIA-Nemotron-Labs-Dory1.0-4B-GGUF:Q5_K_M
RX 7900 XTX 24GBOllamaQ5_K_M4.5 GBfits in fast memory~157 tok/sollama run hf.co/nvidia/NVIDIA-Nemotron-Labs-Dory1.0-4B-GGUF:Q5_K_M
M1 Max (24c GPU) 32GBOllamaQ5_K_M4.5 GBfits in fast memory~87 tok/sollama run hf.co/nvidia/NVIDIA-Nemotron-Labs-Dory1.0-4B-GGUF:Q5_K_M
M1 Max (32c GPU) 32GBOllamaQ5_K_M4.5 GBfits in fast memory~87 tok/sollama run hf.co/nvidia/NVIDIA-Nemotron-Labs-Dory1.0-4B-GGUF:Q5_K_M
M1 Pro 32GBOllamaQ5_K_M4.5 GBfits in fast memory~44 tok/sollama run hf.co/nvidia/NVIDIA-Nemotron-Labs-Dory1.0-4B-GGUF:Q5_K_M
M2 Max (30c GPU) 32GBOllamaQ5_K_M4.5 GBfits in fast memory~87 tok/sollama run hf.co/nvidia/NVIDIA-Nemotron-Labs-Dory1.0-4B-GGUF:Q5_K_M
M2 Max (38c GPU) 32GBOllamaQ5_K_M4.5 GBfits in fast memory~87 tok/sollama run hf.co/nvidia/NVIDIA-Nemotron-Labs-Dory1.0-4B-GGUF:Q5_K_M
M2 Pro 32GBOllamaQ5_K_M4.5 GBfits in fast memory~44 tok/sollama run hf.co/nvidia/NVIDIA-Nemotron-Labs-Dory1.0-4B-GGUF:Q5_K_M
M4 32GBOllamaQ5_K_M4.5 GBfits in fast memory~26 tok/sollama run hf.co/nvidia/NVIDIA-Nemotron-Labs-Dory1.0-4B-GGUF:Q5_K_M
M3 Max (30c GPU) 36GBOllamaQ5_K_M4.5 GBfits in fast memory~65 tok/sollama run hf.co/nvidia/NVIDIA-Nemotron-Labs-Dory1.0-4B-GGUF:Q5_K_M
M3 Pro 36GBOllamaQ5_K_M4.5 GBfits in fast memory~33 tok/sollama run hf.co/nvidia/NVIDIA-Nemotron-Labs-Dory1.0-4B-GGUF:Q5_K_M
M4 Max (32c GPU) 36GBOllamaQ5_K_M4.5 GBfits in fast memory~89 tok/sollama run hf.co/nvidia/NVIDIA-Nemotron-Labs-Dory1.0-4B-GGUF:Q5_K_M
Mac Studio M4 Max (32c GPU) 36GBOllamaQ5_K_M4.5 GBfits in fast memory~89 tok/sollama run hf.co/nvidia/NVIDIA-Nemotron-Labs-Dory1.0-4B-GGUF:Q5_K_M
Mac Studio M5 Max (32c GPU) 36GBOllamaQ5_K_M4.5 GBfits in fast memory~100 tok/sollama run hf.co/nvidia/NVIDIA-Nemotron-Labs-Dory1.0-4B-GGUF:Q5_K_M
RTX 5090 32GBOllamaQ5_K_M4.5 GBfits in fast memory~293 tok/sollama run hf.co/nvidia/NVIDIA-Nemotron-Labs-Dory1.0-4B-GGUF:Q5_K_M
M3 Max (40c GPU) 48GBOllamaQ5_K_M4.5 GBfits in fast memory~87 tok/sollama run hf.co/nvidia/NVIDIA-Nemotron-Labs-Dory1.0-4B-GGUF:Q5_K_M
M4 Max (40c GPU) 48GBOllamaQ5_K_M4.5 GBfits in fast memory~119 tok/sollama run hf.co/nvidia/NVIDIA-Nemotron-Labs-Dory1.0-4B-GGUF:Q5_K_M
M4 Pro 48GBOllamaQ5_K_M4.5 GBfits in fast memory~60 tok/sollama run hf.co/nvidia/NVIDIA-Nemotron-Labs-Dory1.0-4B-GGUF:Q5_K_M
Mac Studio M4 Max (40c GPU) 48GBOllamaQ5_K_M4.5 GBfits in fast memory~119 tok/sollama run hf.co/nvidia/NVIDIA-Nemotron-Labs-Dory1.0-4B-GGUF:Q5_K_M
Mac Studio M5 Max (40c GPU) 48GBOllamaQ5_K_M4.5 GBfits in fast memory~134 tok/sollama run hf.co/nvidia/NVIDIA-Nemotron-Labs-Dory1.0-4B-GGUF:Q5_K_M
M1 Max (32c GPU) 64GBOllamaQ5_K_M4.5 GBfits in fast memory~87 tok/sollama run hf.co/nvidia/NVIDIA-Nemotron-Labs-Dory1.0-4B-GGUF:Q5_K_M
M2 Max (30c GPU) 64GBOllamaQ5_K_M4.5 GBfits in fast memory~87 tok/sollama run hf.co/nvidia/NVIDIA-Nemotron-Labs-Dory1.0-4B-GGUF:Q5_K_M
M2 Max (38c GPU) 64GBOllamaQ5_K_M4.5 GBfits in fast memory~87 tok/sollama run hf.co/nvidia/NVIDIA-Nemotron-Labs-Dory1.0-4B-GGUF:Q5_K_M
M2 Ultra 64GBOllamaQ5_K_M4.5 GBfits in fast memory~174 tok/sollama run hf.co/nvidia/NVIDIA-Nemotron-Labs-Dory1.0-4B-GGUF:Q5_K_M
M3 Max (40c GPU) 64GBOllamaQ5_K_M4.5 GBfits in fast memory~87 tok/sollama run hf.co/nvidia/NVIDIA-Nemotron-Labs-Dory1.0-4B-GGUF:Q5_K_M
M4 Max (40c GPU) 64GBOllamaQ5_K_M4.5 GBfits in fast memory~119 tok/sollama run hf.co/nvidia/NVIDIA-Nemotron-Labs-Dory1.0-4B-GGUF:Q5_K_M
M4 Pro 64GBOllamaQ5_K_M4.5 GBfits in fast memory~60 tok/sollama run hf.co/nvidia/NVIDIA-Nemotron-Labs-Dory1.0-4B-GGUF:Q5_K_M
Mac Studio M4 Max (40c GPU) 64GBOllamaQ5_K_M4.5 GBfits in fast memory~119 tok/sollama run hf.co/nvidia/NVIDIA-Nemotron-Labs-Dory1.0-4B-GGUF:Q5_K_M
Mac Studio M5 Max (40c GPU) 64GBOllamaQ5_K_M4.5 GBfits in fast memory~134 tok/sollama run hf.co/nvidia/NVIDIA-Nemotron-Labs-Dory1.0-4B-GGUF:Q5_K_M
M2 Max (38c GPU) 96GBOllamaQ5_K_M4.5 GBfits in fast memory~87 tok/sollama run hf.co/nvidia/NVIDIA-Nemotron-Labs-Dory1.0-4B-GGUF:Q5_K_M
M3 Max (30c GPU) 96GBOllamaQ5_K_M4.5 GBfits in fast memory~65 tok/sollama run hf.co/nvidia/NVIDIA-Nemotron-Labs-Dory1.0-4B-GGUF:Q5_K_M
Mac Studio M3 Ultra (60c GPU) 96GBOllamaQ5_K_M4.5 GBfits in fast memory~179 tok/sollama run hf.co/nvidia/NVIDIA-Nemotron-Labs-Dory1.0-4B-GGUF:Q5_K_M
Mac Studio M3 Ultra (80c GPU) 96GBOllamaQ5_K_M4.5 GBfits in fast memory~179 tok/sollama run hf.co/nvidia/NVIDIA-Nemotron-Labs-Dory1.0-4B-GGUF:Q5_K_M
Mac Studio M5 Ultra (64c GPU) 96GBOllamaQ5_K_M4.5 GBfits in fast memory~262 tok/sollama run hf.co/nvidia/NVIDIA-Nemotron-Labs-Dory1.0-4B-GGUF:Q5_K_M
Mac Studio M5 Ultra (80c GPU) 96GBOllamaQ5_K_M4.5 GBfits in fast memory~262 tok/sollama run hf.co/nvidia/NVIDIA-Nemotron-Labs-Dory1.0-4B-GGUF:Q5_K_M
M2 Ultra 128GBOllamaQ5_K_M4.5 GBfits in fast memory~174 tok/sollama run hf.co/nvidia/NVIDIA-Nemotron-Labs-Dory1.0-4B-GGUF:Q5_K_M
M3 Max (40c GPU) 128GBOllamaQ5_K_M4.5 GBfits in fast memory~87 tok/sollama run hf.co/nvidia/NVIDIA-Nemotron-Labs-Dory1.0-4B-GGUF:Q5_K_M
M4 Max (40c GPU) 128GBOllamaQ5_K_M4.5 GBfits in fast memory~119 tok/sollama run hf.co/nvidia/NVIDIA-Nemotron-Labs-Dory1.0-4B-GGUF:Q5_K_M
Mac Studio M4 Max (40c GPU) 128GBOllamaQ5_K_M4.5 GBfits in fast memory~119 tok/sollama run hf.co/nvidia/NVIDIA-Nemotron-Labs-Dory1.0-4B-GGUF:Q5_K_M
Mac Studio M5 Max (40c GPU) 128GBOllamaQ5_K_M4.5 GBfits in fast memory~134 tok/sollama run hf.co/nvidia/NVIDIA-Nemotron-Labs-Dory1.0-4B-GGUF:Q5_K_M
DGX Spark 128GB (NVIDIA, ASUS, Dell, Lenovo, HP, MSI, Acer, Gigabyte)OllamaQ5_K_M4.5 GBfits in fast memory~56 tok/sollama run hf.co/nvidia/NVIDIA-Nemotron-Labs-Dory1.0-4B-GGUF:Q5_K_M
M2 Ultra 192GBOllamaQ5_K_M4.5 GBfits in fast memory~174 tok/sollama run hf.co/nvidia/NVIDIA-Nemotron-Labs-Dory1.0-4B-GGUF:Q5_K_M
2x Mac Studio M5 Max (40c GPU) 128GBllama.cppQ5_K_M GGUF4.5 GBfits in fast memory~114 tok/sllama-server -hf nvidia/NVIDIA-Nemotron-Labs-Dory1.0-4B-GGUF:Q5_K_M --rpc node2:50052 -c 8192 # run rpc-server on each other node
Mac Studio M3 Ultra (60c GPU) 256GBOllamaQ5_K_M4.5 GBfits in fast memory~179 tok/sollama run hf.co/nvidia/NVIDIA-Nemotron-Labs-Dory1.0-4B-GGUF:Q5_K_M
Mac Studio M3 Ultra (80c GPU) 256GBOllamaQ5_K_M4.5 GBfits in fast memory~179 tok/sollama run hf.co/nvidia/NVIDIA-Nemotron-Labs-Dory1.0-4B-GGUF:Q5_K_M
Mac Studio M5 Ultra (64c GPU) 256GBOllamaQ5_K_M4.5 GBfits in fast memory~262 tok/sollama run hf.co/nvidia/NVIDIA-Nemotron-Labs-Dory1.0-4B-GGUF:Q5_K_M
Mac Studio M5 Ultra (80c GPU) 256GBOllamaQ5_K_M4.5 GBfits in fast memory~262 tok/sollama run hf.co/nvidia/NVIDIA-Nemotron-Labs-Dory1.0-4B-GGUF:Q5_K_M
2x DGX Spark 128GBllama.cppQ5_K_M GGUF4.5 GBfits in fast memory~47 tok/sllama-server -hf nvidia/NVIDIA-Nemotron-Labs-Dory1.0-4B-GGUF:Q5_K_M --rpc node2:50052 -c 8192 # run rpc-server on each other node
4x Mac Studio M5 Max (40c GPU) 128GBllama.cppQ5_K_M GGUF4.5 GBfits in fast memory~100 tok/sllama-server -hf nvidia/NVIDIA-Nemotron-Labs-Dory1.0-4B-GGUF:Q5_K_M --rpc node2:50052,node3:50052,node4:50052 -c 8192 # run rpc-server on each other node
2x Mac Studio M5 Ultra (80c GPU) 256GBllama.cppQ5_K_M GGUF4.5 GBfits in fast memory~222 tok/sllama-server -hf nvidia/NVIDIA-Nemotron-Labs-Dory1.0-4B-GGUF:Q5_K_M --rpc node2:50052 -c 8192 # run rpc-server on each other node
Mac Studio M3 Ultra (80c GPU) 512GBOllamaQ5_K_M4.5 GBfits in fast memory~179 tok/sollama run hf.co/nvidia/NVIDIA-Nemotron-Labs-Dory1.0-4B-GGUF:Q5_K_M
4x DGX Spark 128GBllama.cppQ5_K_M GGUF4.5 GBfits in fast memory~42 tok/sllama-server -hf nvidia/NVIDIA-Nemotron-Labs-Dory1.0-4B-GGUF:Q5_K_M --rpc node2:50052,node3:50052,node4:50052 -c 8192 # run rpc-server on each other node
4x Mac Studio M5 Ultra (80c GPU) 256GBllama.cppQ5_K_M GGUF4.5 GBfits in fast memory~196 tok/sllama-server -hf nvidia/NVIDIA-Nemotron-Labs-Dory1.0-4B-GGUF:Q5_K_M --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 2026-10-20.

A project by OnDevice Labs · llms.txt