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Can I run Llama 3.2 3B locally?

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Ollama weight files: Q4_K_M 2 GB (llama3.2:3b); Q5_K_M 2.3 GB (llama3.2:3b-instruct-q5_K_M); Q8_0 3.4 GB (llama3.2:3b-instruct-q8_0).

Yes on 62 machines in this list. The smallest is M1 8GB: Q8_0, about 4.2 GB, roughly 16 tokens per second, via Ollama. ollama run llama3.2:3b-instruct-q8_0

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

Open Llama 3.2 3B in the checker

Hardware that fits

HardwareRuntimeQuantMemoryFitSpeedCommand
M1 8GBOllamaQ8_04.2 GBfits in fast memory~16 tok/sollama run llama3.2:3b-instruct-q8_0
M2 8GBOllamaQ8_04.2 GBfits in fast memory~24 tok/sollama run llama3.2:3b-instruct-q8_0
M3 8GBOllamaQ8_04.2 GBfits in fast memory~24 tok/sollama run llama3.2:3b-instruct-q8_0
RTX 3060 Ti 8GBOllamaQ8_04.2 GBfits in fast memory~79 tok/sollama run llama3.2:3b-instruct-q8_0
RTX 3070 8GBOllamaQ8_04.2 GBfits in fast memory~79 tok/sollama run llama3.2:3b-instruct-q8_0
RTX 4060 8GBOllamaQ8_04.2 GBfits in fast memory~48 tok/sollama run llama3.2:3b-instruct-q8_0
RX 7600 8GBOllamaQ8_04.2 GBfits in fast memory~51 tok/sollama run llama3.2:3b-instruct-q8_0
RTX 3080 10GBOllamaQ8_04.2 GBfits in fast memory~134 tok/sollama run llama3.2:3b-instruct-q8_0
M1 16GBOllamaQ8_04.2 GBfits in fast memory~16 tok/sollama run llama3.2:3b-instruct-q8_0
M2 16GBOllamaQ8_04.2 GBfits in fast memory~24 tok/sollama run llama3.2:3b-instruct-q8_0
M3 16GBOllamaQ8_04.2 GBfits in fast memory~24 tok/sollama run llama3.2:3b-instruct-q8_0
M4 16GBOllamaQ8_04.2 GBfits in fast memory~28 tok/sollama run llama3.2:3b-instruct-q8_0
RTX 3060 12GBOllamaQ8_04.2 GBfits in fast memory~64 tok/sollama run llama3.2:3b-instruct-q8_0
RTX 4070 12GBOllamaQ8_04.2 GBfits in fast memory~89 tok/sollama run llama3.2:3b-instruct-q8_0
RTX 5070 12GBOllamaQ8_04.2 GBfits in fast memory~119 tok/sollama run llama3.2:3b-instruct-q8_0
RTX 4060 Ti 16GBOllamaQ8_04.2 GBfits in fast memory~51 tok/sollama run llama3.2:3b-instruct-q8_0
RTX 4070 Ti Super 16GBOllamaQ8_04.2 GBfits in fast memory~119 tok/sollama run llama3.2:3b-instruct-q8_0
RTX 4080 16GBOllamaQ8_04.2 GBfits in fast memory~127 tok/sollama run llama3.2:3b-instruct-q8_0
RTX 5080 16GBOllamaQ8_04.2 GBfits in fast memory~169 tok/sollama run llama3.2:3b-instruct-q8_0
RX 7800 XT 16GBOllamaQ8_04.2 GBfits in fast memory~110 tok/sollama run llama3.2:3b-instruct-q8_0
RX 9070 XT 16GBOllamaQ8_04.2 GBfits in fast memory~113 tok/sollama run llama3.2:3b-instruct-q8_0
M2 24GBOllamaQ8_04.2 GBfits in fast memory~24 tok/sollama run llama3.2:3b-instruct-q8_0
M3 24GBOllamaQ8_04.2 GBfits in fast memory~24 tok/sollama run llama3.2:3b-instruct-q8_0
M4 24GBOllamaQ8_04.2 GBfits in fast memory~28 tok/sollama run llama3.2:3b-instruct-q8_0
RTX 3090 24GBOllamaQ8_04.2 GBfits in fast memory~165 tok/sollama run llama3.2:3b-instruct-q8_0
RTX 4090 24GBOllamaQ8_04.2 GBfits in fast memory~178 tok/sollama run llama3.2:3b-instruct-q8_0
RX 7900 XTX 24GBOllamaQ8_04.2 GBfits in fast memory~169 tok/sollama run llama3.2:3b-instruct-q8_0
M1 Pro 32GBOllamaQ8_04.2 GBfits in fast memory~47 tok/sollama run llama3.2:3b-instruct-q8_0
M2 Pro 32GBOllamaQ8_04.2 GBfits in fast memory~47 tok/sollama run llama3.2:3b-instruct-q8_0
M4 32GBOllamaQ8_04.2 GBfits in fast memory~28 tok/sollama run llama3.2:3b-instruct-q8_0
M3 Pro 36GBOllamaQ8_04.2 GBfits in fast memory~35 tok/sollama run llama3.2:3b-instruct-q8_0
Mac Studio M4 Max (32c GPU) 36GBOllamaQ8_04.2 GBfits in fast memory~96 tok/sollama run llama3.2:3b-instruct-q8_0
Mac Studio M5 Max (32c GPU) 36GBOllamaQ8_04.2 GBfits in fast memory~108 tok/sollama run llama3.2:3b-instruct-q8_0
RTX 5090 32GBOllamaQ8_04.2 GBfits in fast memory~316 tok/sollama run llama3.2:3b-instruct-q8_0
M4 Pro 48GBOllamaQ8_04.2 GBfits in fast memory~64 tok/sollama run llama3.2:3b-instruct-q8_0
Mac Studio M4 Max (40c GPU) 48GBOllamaQ8_04.2 GBfits in fast memory~128 tok/sollama run llama3.2:3b-instruct-q8_0
Mac Studio M5 Max (40c GPU) 48GBOllamaQ8_04.2 GBfits in fast memory~144 tok/sollama run llama3.2:3b-instruct-q8_0
M1 Max 64GBOllamaQ8_04.2 GBfits in fast memory~94 tok/sollama run llama3.2:3b-instruct-q8_0
M2 Max 64GBOllamaQ8_04.2 GBfits in fast memory~94 tok/sollama run llama3.2:3b-instruct-q8_0
M3 Max 64GBOllamaQ8_04.2 GBfits in fast memory~94 tok/sollama run llama3.2:3b-instruct-q8_0
M4 Max 64GBOllamaQ8_04.2 GBfits in fast memory~128 tok/sollama run llama3.2:3b-instruct-q8_0
Mac Studio M4 Max (40c GPU) 64GBOllamaQ8_04.2 GBfits in fast memory~128 tok/sollama run llama3.2:3b-instruct-q8_0
Mac Studio M5 Max (40c GPU) 64GBOllamaQ8_04.2 GBfits in fast memory~144 tok/sollama run llama3.2:3b-instruct-q8_0
DGX Spark 64GB (ASUS, Dell, HP, MSI, Acer, Gigabyte)OllamaQ8_04.2 GBfits in fast memory~60 tok/sollama run llama3.2:3b-instruct-q8_0
Mac Studio M3 Ultra 96GBOllamaQ8_04.2 GBfits in fast memory~193 tok/sollama run llama3.2:3b-instruct-q8_0
Mac Studio M5 Ultra 96GBOllamaQ8_04.2 GBfits in fast memory~282 tok/sollama run llama3.2:3b-instruct-q8_0
M3 Max 128GBOllamaQ8_04.2 GBfits in fast memory~94 tok/sollama run llama3.2:3b-instruct-q8_0
M4 Max 128GBOllamaQ8_04.2 GBfits in fast memory~128 tok/sollama run llama3.2:3b-instruct-q8_0
Mac Studio M4 Max (40c GPU) 128GBOllamaQ8_04.2 GBfits in fast memory~128 tok/sollama run llama3.2:3b-instruct-q8_0
Mac Studio M5 Max (40c GPU) 128GBOllamaQ8_04.2 GBfits in fast memory~144 tok/sollama run llama3.2:3b-instruct-q8_0
DGX Spark 128GB (NVIDIA, ASUS, Dell, Lenovo, HP, MSI, Acer, Gigabyte)OllamaQ8_04.2 GBfits in fast memory~60 tok/sollama run llama3.2:3b-instruct-q8_0
M2 Ultra 192GBOllamaQ8_04.2 GBfits in fast memory~188 tok/sollama run llama3.2:3b-instruct-q8_0
2x Mac Studio M5 Max (40c GPU) 128GBllama.cppQ8_0 GGUF4.2 GBfits in fast memory~122 tok/sllama-server -hf unsloth/Llama-3.2-3B-Instruct-GGUF:Q8_0 --rpc node2:50052 -c 8192 # run rpc-server on each other node
Mac Studio M3 Ultra 256GBOllamaQ8_04.2 GBfits in fast memory~193 tok/sollama run llama3.2:3b-instruct-q8_0
Mac Studio M5 Ultra (64c GPU) 256GBOllamaQ8_04.2 GBfits in fast memory~282 tok/sollama run llama3.2:3b-instruct-q8_0
Mac Studio M5 Ultra (80c GPU) 256GBOllamaQ8_04.2 GBfits in fast memory~282 tok/sollama run llama3.2:3b-instruct-q8_0
2x DGX Spark 128GBllama.cppQ8_0 GGUF4.2 GBfits in fast memory~51 tok/sllama-server -hf unsloth/Llama-3.2-3B-Instruct-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 GGUF4.2 GBfits in fast memory~108 tok/sllama-server -hf unsloth/Llama-3.2-3B-Instruct-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 GGUF4.2 GBfits in fast memory~239 tok/sllama-server -hf unsloth/Llama-3.2-3B-Instruct-GGUF:Q8_0 --rpc node2:50052 -c 8192 # run rpc-server on each other node
Mac Studio M3 Ultra (80c GPU) 512GBOllamaQ8_04.2 GBfits in fast memory~193 tok/sollama run llama3.2:3b-instruct-q8_0
4x DGX Spark 128GBllama.cppQ8_0 GGUF4.2 GBfits in fast memory~45 tok/sllama-server -hf unsloth/Llama-3.2-3B-Instruct-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 GGUF4.2 GBfits in fast memory~211 tok/sllama-server -hf unsloth/Llama-3.2-3B-Instruct-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.

A project by OnDevice Labs · llms.txt