← CanIRunLocal · All hardware · All models
Alibaba · 1.54B parameters · coding.
Ollama weight files: Q4_K_M 0.99 GB (qwen2.5-coder:1.5b); Q5_K_M 1.1 GB (qwen2.5-coder:1.5b-instruct-q5_K_M); Q8_0 1.6 GB (qwen2.5-coder:1.5b-instruct-q8_0).
Yes on 62 machines in this list. The smallest is M1 8GB: Q8_0, about 2.3 GB, roughly 34 tokens per second, via Ollama. ollama run qwen2.5-coder:1.5b-instruct-q8_0
ollama run qwen2.5-coder:1.5b-instruct-q8_0ollama run qwen2.5-coder:1.5b-instruct-q8_0ollama run qwen2.5-coder:1.5b-instruct-q8_0ollama run qwen2.5-coder:1.5b-instruct-q8_0lms get unsloth/Qwen2.5-Coder-1.5B-Instruct-GGUF@Q8_0llama-server -hf unsloth/Qwen2.5-Coder-1.5B-Instruct-GGUF:Q8_0 -c 8192vllm serve Qwen/Qwen2.5-Coder-1.5B-Instruct --max-model-len 8192 --gpu-memory-utilization 0.9| Hardware | Runtime | Quant | Memory | Fit | Speed | Command |
|---|---|---|---|---|---|---|
| M1 8GB | Ollama | Q8_0 | 2.3 GB | fits in fast memory | ~34 tok/s | ollama run qwen2.5-coder:1.5b-instruct-q8_0 |
| M2 8GB | Ollama | Q8_0 | 2.3 GB | fits in fast memory | ~50 tok/s | ollama run qwen2.5-coder:1.5b-instruct-q8_0 |
| M3 8GB | Ollama | Q8_0 | 2.3 GB | fits in fast memory | ~50 tok/s | ollama run qwen2.5-coder:1.5b-instruct-q8_0 |
| RTX 3060 Ti 8GB | Ollama | Q8_0 | 2.3 GB | fits in fast memory | ~168 tok/s | ollama run qwen2.5-coder:1.5b-instruct-q8_0 |
| RTX 3070 8GB | Ollama | Q8_0 | 2.3 GB | fits in fast memory | ~168 tok/s | ollama run qwen2.5-coder:1.5b-instruct-q8_0 |
| RTX 4060 8GB | Ollama | Q8_0 | 2.3 GB | fits in fast memory | ~102 tok/s | ollama run qwen2.5-coder:1.5b-instruct-q8_0 |
| RX 7600 8GB | Ollama | Q8_0 | 2.3 GB | fits in fast memory | ~108 tok/s | ollama run qwen2.5-coder:1.5b-instruct-q8_0 |
| RTX 3080 10GB | Ollama | Q8_0 | 2.3 GB | fits in fast memory | ~285 tok/s | ollama run qwen2.5-coder:1.5b-instruct-q8_0 |
| M1 16GB | Ollama | Q8_0 | 2.3 GB | fits in fast memory | ~34 tok/s | ollama run qwen2.5-coder:1.5b-instruct-q8_0 |
| M2 16GB | Ollama | Q8_0 | 2.3 GB | fits in fast memory | ~50 tok/s | ollama run qwen2.5-coder:1.5b-instruct-q8_0 |
| M3 16GB | Ollama | Q8_0 | 2.3 GB | fits in fast memory | ~50 tok/s | ollama run qwen2.5-coder:1.5b-instruct-q8_0 |
| M4 16GB | Ollama | Q8_0 | 2.3 GB | fits in fast memory | ~60 tok/s | ollama run qwen2.5-coder:1.5b-instruct-q8_0 |
| RTX 3060 12GB | Ollama | Q8_0 | 2.3 GB | fits in fast memory | ~135 tok/s | ollama run qwen2.5-coder:1.5b-instruct-q8_0 |
| RTX 4070 12GB | Ollama | Q8_0 | 2.3 GB | fits in fast memory | ~189 tok/s | ollama run qwen2.5-coder:1.5b-instruct-q8_0 |
| RTX 5070 12GB | Ollama | Q8_0 | 2.3 GB | fits in fast memory | ~252 tok/s | ollama run qwen2.5-coder:1.5b-instruct-q8_0 |
| RTX 4060 Ti 16GB | Ollama | Q8_0 | 2.3 GB | fits in fast memory | ~108 tok/s | ollama run qwen2.5-coder:1.5b-instruct-q8_0 |
| RTX 4070 Ti Super 16GB | Ollama | Q8_0 | 2.3 GB | fits in fast memory | ~252 tok/s | ollama run qwen2.5-coder:1.5b-instruct-q8_0 |
| RTX 4080 16GB | Ollama | Q8_0 | 2.3 GB | fits in fast memory | ~269 tok/s | ollama run qwen2.5-coder:1.5b-instruct-q8_0 |
| RTX 5080 16GB | Ollama | Q8_0 | 2.3 GB | fits in fast memory | ~360 tok/s | ollama run qwen2.5-coder:1.5b-instruct-q8_0 |
| RX 7800 XT 16GB | Ollama | Q8_0 | 2.3 GB | fits in fast memory | ~234 tok/s | ollama run qwen2.5-coder:1.5b-instruct-q8_0 |
| RX 9070 XT 16GB | Ollama | Q8_0 | 2.3 GB | fits in fast memory | ~240 tok/s | ollama run qwen2.5-coder:1.5b-instruct-q8_0 |
| M2 24GB | Ollama | Q8_0 | 2.3 GB | fits in fast memory | ~50 tok/s | ollama run qwen2.5-coder:1.5b-instruct-q8_0 |
| M3 24GB | Ollama | Q8_0 | 2.3 GB | fits in fast memory | ~50 tok/s | ollama run qwen2.5-coder:1.5b-instruct-q8_0 |
| M4 24GB | Ollama | Q8_0 | 2.3 GB | fits in fast memory | ~60 tok/s | ollama run qwen2.5-coder:1.5b-instruct-q8_0 |
| RTX 3090 24GB | Ollama | Q8_0 | 2.3 GB | fits in fast memory | ~351 tok/s | ollama run qwen2.5-coder:1.5b-instruct-q8_0 |
| RTX 4090 24GB | Ollama | Q8_0 | 2.3 GB | fits in fast memory | ~378 tok/s | ollama run qwen2.5-coder:1.5b-instruct-q8_0 |
| RX 7900 XTX 24GB | Ollama | Q8_0 | 2.3 GB | fits in fast memory | ~360 tok/s | ollama run qwen2.5-coder:1.5b-instruct-q8_0 |
| M1 Pro 32GB | Ollama | Q8_0 | 2.3 GB | fits in fast memory | ~100 tok/s | ollama run qwen2.5-coder:1.5b-instruct-q8_0 |
| M2 Pro 32GB | Ollama | Q8_0 | 2.3 GB | fits in fast memory | ~100 tok/s | ollama run qwen2.5-coder:1.5b-instruct-q8_0 |
| M4 32GB | Ollama | Q8_0 | 2.3 GB | fits in fast memory | ~60 tok/s | ollama run qwen2.5-coder:1.5b-instruct-q8_0 |
| M3 Pro 36GB | Ollama | Q8_0 | 2.3 GB | fits in fast memory | ~75 tok/s | ollama run qwen2.5-coder:1.5b-instruct-q8_0 |
| Mac Studio M4 Max (32c GPU) 36GB | Ollama | Q8_0 | 2.3 GB | fits in fast memory | ~205 tok/s | ollama run qwen2.5-coder:1.5b-instruct-q8_0 |
| Mac Studio M5 Max (32c GPU) 36GB | Ollama | Q8_0 | 2.3 GB | fits in fast memory | ~230 tok/s | ollama run qwen2.5-coder:1.5b-instruct-q8_0 |
| RTX 5090 32GB | Ollama | Q8_0 | 2.3 GB | fits in fast memory | ~672 tok/s | ollama run qwen2.5-coder:1.5b-instruct-q8_0 |
| M4 Pro 48GB | Ollama | Q8_0 | 2.3 GB | fits in fast memory | ~137 tok/s | ollama run qwen2.5-coder:1.5b-instruct-q8_0 |
| Mac Studio M4 Max (40c GPU) 48GB | Ollama | Q8_0 | 2.3 GB | fits in fast memory | ~273 tok/s | ollama run qwen2.5-coder:1.5b-instruct-q8_0 |
| Mac Studio M5 Max (40c GPU) 48GB | Ollama | Q8_0 | 2.3 GB | fits in fast memory | ~307 tok/s | ollama run qwen2.5-coder:1.5b-instruct-q8_0 |
| M1 Max 64GB | Ollama | Q8_0 | 2.3 GB | fits in fast memory | ~200 tok/s | ollama run qwen2.5-coder:1.5b-instruct-q8_0 |
| M2 Max 64GB | Ollama | Q8_0 | 2.3 GB | fits in fast memory | ~200 tok/s | ollama run qwen2.5-coder:1.5b-instruct-q8_0 |
| M3 Max 64GB | Ollama | Q8_0 | 2.3 GB | fits in fast memory | ~200 tok/s | ollama run qwen2.5-coder:1.5b-instruct-q8_0 |
| M4 Max 64GB | Ollama | Q8_0 | 2.3 GB | fits in fast memory | ~273 tok/s | ollama run qwen2.5-coder:1.5b-instruct-q8_0 |
| Mac Studio M4 Max (40c GPU) 64GB | Ollama | Q8_0 | 2.3 GB | fits in fast memory | ~273 tok/s | ollama run qwen2.5-coder:1.5b-instruct-q8_0 |
| Mac Studio M5 Max (40c GPU) 64GB | Ollama | Q8_0 | 2.3 GB | fits in fast memory | ~307 tok/s | ollama run qwen2.5-coder:1.5b-instruct-q8_0 |
| DGX Spark 64GB (ASUS, Dell, HP, MSI, Acer, Gigabyte) | Ollama | Q8_0 | 2.3 GB | fits in fast memory | ~128 tok/s | ollama run qwen2.5-coder:1.5b-instruct-q8_0 |
| Mac Studio M3 Ultra 96GB | Ollama | Q8_0 | 2.3 GB | fits in fast memory | ~410 tok/s | ollama run qwen2.5-coder:1.5b-instruct-q8_0 |
| Mac Studio M5 Ultra 96GB | Ollama | Q8_0 | 2.3 GB | fits in fast memory | ~600 tok/s | ollama run qwen2.5-coder:1.5b-instruct-q8_0 |
| M3 Max 128GB | Ollama | Q8_0 | 2.3 GB | fits in fast memory | ~200 tok/s | ollama run qwen2.5-coder:1.5b-instruct-q8_0 |
| M4 Max 128GB | Ollama | Q8_0 | 2.3 GB | fits in fast memory | ~273 tok/s | ollama run qwen2.5-coder:1.5b-instruct-q8_0 |
| Mac Studio M4 Max (40c GPU) 128GB | Ollama | Q8_0 | 2.3 GB | fits in fast memory | ~273 tok/s | ollama run qwen2.5-coder:1.5b-instruct-q8_0 |
| Mac Studio M5 Max (40c GPU) 128GB | Ollama | Q8_0 | 2.3 GB | fits in fast memory | ~307 tok/s | ollama run qwen2.5-coder:1.5b-instruct-q8_0 |
| DGX Spark 128GB (NVIDIA, ASUS, Dell, Lenovo, HP, MSI, Acer, Gigabyte) | Ollama | Q8_0 | 2.3 GB | fits in fast memory | ~128 tok/s | ollama run qwen2.5-coder:1.5b-instruct-q8_0 |
| M2 Ultra 192GB | Ollama | Q8_0 | 2.3 GB | fits in fast memory | ~400 tok/s | ollama run qwen2.5-coder:1.5b-instruct-q8_0 |
| 2x Mac Studio M5 Max (40c GPU) 128GB | llama.cpp | Q8_0 GGUF | 2.3 GB | fits in fast memory | ~253 tok/s | llama-server -hf unsloth/Qwen2.5-Coder-1.5B-Instruct-GGUF:Q8_0 --rpc node2:50052 -c 8192 # run rpc-server on each other node |
| Mac Studio M3 Ultra 256GB | Ollama | Q8_0 | 2.3 GB | fits in fast memory | ~410 tok/s | ollama run qwen2.5-coder:1.5b-instruct-q8_0 |
| Mac Studio M5 Ultra (64c GPU) 256GB | Ollama | Q8_0 | 2.3 GB | fits in fast memory | ~600 tok/s | ollama run qwen2.5-coder:1.5b-instruct-q8_0 |
| Mac Studio M5 Ultra (80c GPU) 256GB | Ollama | Q8_0 | 2.3 GB | fits in fast memory | ~600 tok/s | ollama run qwen2.5-coder:1.5b-instruct-q8_0 |
| 2x DGX Spark 128GB | llama.cpp | Q8_0 GGUF | 2.3 GB | fits in fast memory | ~105 tok/s | llama-server -hf unsloth/Qwen2.5-Coder-1.5B-Instruct-GGUF:Q8_0 --rpc node2:50052 -c 8192 # run rpc-server on each other node |
| 4x Mac Studio M5 Max (40c GPU) 128GB | llama.cpp | Q8_0 GGUF | 2.3 GB | fits in fast memory | ~223 tok/s | llama-server -hf unsloth/Qwen2.5-Coder-1.5B-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) 256GB | llama.cpp | Q8_0 GGUF | 2.3 GB | fits in fast memory | ~495 tok/s | llama-server -hf unsloth/Qwen2.5-Coder-1.5B-Instruct-GGUF:Q8_0 --rpc node2:50052 -c 8192 # run rpc-server on each other node |
| Mac Studio M3 Ultra (80c GPU) 512GB | Ollama | Q8_0 | 2.3 GB | fits in fast memory | ~410 tok/s | ollama run qwen2.5-coder:1.5b-instruct-q8_0 |
| 4x DGX Spark 128GB | llama.cpp | Q8_0 GGUF | 2.3 GB | fits in fast memory | ~93 tok/s | llama-server -hf unsloth/Qwen2.5-Coder-1.5B-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) 256GB | llama.cpp | Q8_0 GGUF | 2.3 GB | fits in fast memory | ~436 tok/s | llama-server -hf unsloth/Qwen2.5-Coder-1.5B-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