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Liquid AI · 1.17B parameters · chat, reasoning.
Ollama weight files: Q4_K_M 0.73 GB (lfm2.5-thinking:1.2b); Q8_0 1.2 GB (lfm2.5-thinking:1.2b-q8_0).
Yes on 62 machines in this list. The smallest is M1 8GB: Q8_0, about 1.9 GB, roughly 45 tokens per second, via Ollama. ollama run lfm2.5-thinking:1.2b-q8_0
ollama run lfm2.5-thinking:1.2b-q8_0ollama run lfm2.5-thinking:1.2b-q8_0ollama run lfm2.5-thinking:1.2b-q8_0ollama run lfm2.5-thinking:1.2b-q8_0lms get unsloth/LFM2.5-1.2B-Thinking-GGUF@Q8_0llama-server -hf unsloth/LFM2.5-1.2B-Thinking-GGUF:Q8_0 -c 8192vllm serve LiquidAI/LFM2.5-1.2B-Thinking --max-model-len 8192 --gpu-memory-utilization 0.9| Hardware | Runtime | Quant | Memory | Fit | Speed | Command |
|---|---|---|---|---|---|---|
| M1 8GB | Ollama | Q8_0 | 1.9 GB | fits in fast memory | ~45 tok/s | ollama run lfm2.5-thinking:1.2b-q8_0 |
| M2 8GB | Ollama | Q8_0 | 1.9 GB | fits in fast memory | ~67 tok/s | ollama run lfm2.5-thinking:1.2b-q8_0 |
| M3 8GB | Ollama | Q8_0 | 1.9 GB | fits in fast memory | ~67 tok/s | ollama run lfm2.5-thinking:1.2b-q8_0 |
| RTX 3060 Ti 8GB | Ollama | Q8_0 | 1.9 GB | fits in fast memory | ~224 tok/s | ollama run lfm2.5-thinking:1.2b-q8_0 |
| RTX 3070 8GB | Ollama | Q8_0 | 1.9 GB | fits in fast memory | ~224 tok/s | ollama run lfm2.5-thinking:1.2b-q8_0 |
| RTX 4060 8GB | Ollama | Q8_0 | 1.9 GB | fits in fast memory | ~136 tok/s | ollama run lfm2.5-thinking:1.2b-q8_0 |
| RX 7600 8GB | Ollama | Q8_0 | 1.9 GB | fits in fast memory | ~144 tok/s | ollama run lfm2.5-thinking:1.2b-q8_0 |
| RTX 3080 10GB | Ollama | Q8_0 | 1.9 GB | fits in fast memory | ~380 tok/s | ollama run lfm2.5-thinking:1.2b-q8_0 |
| M1 16GB | Ollama | Q8_0 | 1.9 GB | fits in fast memory | ~45 tok/s | ollama run lfm2.5-thinking:1.2b-q8_0 |
| M2 16GB | Ollama | Q8_0 | 1.9 GB | fits in fast memory | ~67 tok/s | ollama run lfm2.5-thinking:1.2b-q8_0 |
| M3 16GB | Ollama | Q8_0 | 1.9 GB | fits in fast memory | ~67 tok/s | ollama run lfm2.5-thinking:1.2b-q8_0 |
| M4 16GB | Ollama | Q8_0 | 1.9 GB | fits in fast memory | ~80 tok/s | ollama run lfm2.5-thinking:1.2b-q8_0 |
| RTX 3060 12GB | Ollama | Q8_0 | 1.9 GB | fits in fast memory | ~180 tok/s | ollama run lfm2.5-thinking:1.2b-q8_0 |
| RTX 4070 12GB | Ollama | Q8_0 | 1.9 GB | fits in fast memory | ~252 tok/s | ollama run lfm2.5-thinking:1.2b-q8_0 |
| RTX 5070 12GB | Ollama | Q8_0 | 1.9 GB | fits in fast memory | ~336 tok/s | ollama run lfm2.5-thinking:1.2b-q8_0 |
| RTX 4060 Ti 16GB | Ollama | Q8_0 | 1.9 GB | fits in fast memory | ~144 tok/s | ollama run lfm2.5-thinking:1.2b-q8_0 |
| RTX 4070 Ti Super 16GB | Ollama | Q8_0 | 1.9 GB | fits in fast memory | ~336 tok/s | ollama run lfm2.5-thinking:1.2b-q8_0 |
| RTX 4080 16GB | Ollama | Q8_0 | 1.9 GB | fits in fast memory | ~359 tok/s | ollama run lfm2.5-thinking:1.2b-q8_0 |
| RTX 5080 16GB | Ollama | Q8_0 | 1.9 GB | fits in fast memory | ~480 tok/s | ollama run lfm2.5-thinking:1.2b-q8_0 |
| RX 7800 XT 16GB | Ollama | Q8_0 | 1.9 GB | fits in fast memory | ~312 tok/s | ollama run lfm2.5-thinking:1.2b-q8_0 |
| RX 9070 XT 16GB | Ollama | Q8_0 | 1.9 GB | fits in fast memory | ~320 tok/s | ollama run lfm2.5-thinking:1.2b-q8_0 |
| M2 24GB | Ollama | Q8_0 | 1.9 GB | fits in fast memory | ~67 tok/s | ollama run lfm2.5-thinking:1.2b-q8_0 |
| M3 24GB | Ollama | Q8_0 | 1.9 GB | fits in fast memory | ~67 tok/s | ollama run lfm2.5-thinking:1.2b-q8_0 |
| M4 24GB | Ollama | Q8_0 | 1.9 GB | fits in fast memory | ~80 tok/s | ollama run lfm2.5-thinking:1.2b-q8_0 |
| RTX 3090 24GB | Ollama | Q8_0 | 1.9 GB | fits in fast memory | ~468 tok/s | ollama run lfm2.5-thinking:1.2b-q8_0 |
| RTX 4090 24GB | Ollama | Q8_0 | 1.9 GB | fits in fast memory | ~504 tok/s | ollama run lfm2.5-thinking:1.2b-q8_0 |
| RX 7900 XTX 24GB | Ollama | Q8_0 | 1.9 GB | fits in fast memory | ~480 tok/s | ollama run lfm2.5-thinking:1.2b-q8_0 |
| M1 Pro 32GB | Ollama | Q8_0 | 1.9 GB | fits in fast memory | ~133 tok/s | ollama run lfm2.5-thinking:1.2b-q8_0 |
| M2 Pro 32GB | Ollama | Q8_0 | 1.9 GB | fits in fast memory | ~133 tok/s | ollama run lfm2.5-thinking:1.2b-q8_0 |
| M4 32GB | Ollama | Q8_0 | 1.9 GB | fits in fast memory | ~80 tok/s | ollama run lfm2.5-thinking:1.2b-q8_0 |
| M3 Pro 36GB | Ollama | Q8_0 | 1.9 GB | fits in fast memory | ~100 tok/s | ollama run lfm2.5-thinking:1.2b-q8_0 |
| Mac Studio M4 Max (32c GPU) 36GB | Ollama | Q8_0 | 1.9 GB | fits in fast memory | ~273 tok/s | ollama run lfm2.5-thinking:1.2b-q8_0 |
| Mac Studio M5 Max (32c GPU) 36GB | Ollama | Q8_0 | 1.9 GB | fits in fast memory | ~307 tok/s | ollama run lfm2.5-thinking:1.2b-q8_0 |
| RTX 5090 32GB | Ollama | Q8_0 | 1.9 GB | fits in fast memory | ~896 tok/s | ollama run lfm2.5-thinking:1.2b-q8_0 |
| M4 Pro 48GB | Ollama | Q8_0 | 1.9 GB | fits in fast memory | ~182 tok/s | ollama run lfm2.5-thinking:1.2b-q8_0 |
| Mac Studio M4 Max (40c GPU) 48GB | Ollama | Q8_0 | 1.9 GB | fits in fast memory | ~364 tok/s | ollama run lfm2.5-thinking:1.2b-q8_0 |
| Mac Studio M5 Max (40c GPU) 48GB | Ollama | Q8_0 | 1.9 GB | fits in fast memory | ~409 tok/s | ollama run lfm2.5-thinking:1.2b-q8_0 |
| M1 Max 64GB | Ollama | Q8_0 | 1.9 GB | fits in fast memory | ~267 tok/s | ollama run lfm2.5-thinking:1.2b-q8_0 |
| M2 Max 64GB | Ollama | Q8_0 | 1.9 GB | fits in fast memory | ~267 tok/s | ollama run lfm2.5-thinking:1.2b-q8_0 |
| M3 Max 64GB | Ollama | Q8_0 | 1.9 GB | fits in fast memory | ~267 tok/s | ollama run lfm2.5-thinking:1.2b-q8_0 |
| M4 Max 64GB | Ollama | Q8_0 | 1.9 GB | fits in fast memory | ~364 tok/s | ollama run lfm2.5-thinking:1.2b-q8_0 |
| Mac Studio M4 Max (40c GPU) 64GB | Ollama | Q8_0 | 1.9 GB | fits in fast memory | ~364 tok/s | ollama run lfm2.5-thinking:1.2b-q8_0 |
| Mac Studio M5 Max (40c GPU) 64GB | Ollama | Q8_0 | 1.9 GB | fits in fast memory | ~409 tok/s | ollama run lfm2.5-thinking:1.2b-q8_0 |
| DGX Spark 64GB (ASUS, Dell, HP, MSI, Acer, Gigabyte) | Ollama | Q8_0 | 1.9 GB | fits in fast memory | ~171 tok/s | ollama run lfm2.5-thinking:1.2b-q8_0 |
| Mac Studio M3 Ultra 96GB | Ollama | Q8_0 | 1.9 GB | fits in fast memory | ~546 tok/s | ollama run lfm2.5-thinking:1.2b-q8_0 |
| Mac Studio M5 Ultra 96GB | Ollama | Q8_0 | 1.9 GB | fits in fast memory | ~800 tok/s | ollama run lfm2.5-thinking:1.2b-q8_0 |
| M3 Max 128GB | Ollama | Q8_0 | 1.9 GB | fits in fast memory | ~267 tok/s | ollama run lfm2.5-thinking:1.2b-q8_0 |
| M4 Max 128GB | Ollama | Q8_0 | 1.9 GB | fits in fast memory | ~364 tok/s | ollama run lfm2.5-thinking:1.2b-q8_0 |
| Mac Studio M4 Max (40c GPU) 128GB | Ollama | Q8_0 | 1.9 GB | fits in fast memory | ~364 tok/s | ollama run lfm2.5-thinking:1.2b-q8_0 |
| Mac Studio M5 Max (40c GPU) 128GB | Ollama | Q8_0 | 1.9 GB | fits in fast memory | ~409 tok/s | ollama run lfm2.5-thinking:1.2b-q8_0 |
| DGX Spark 128GB (NVIDIA, ASUS, Dell, Lenovo, HP, MSI, Acer, Gigabyte) | Ollama | Q8_0 | 1.9 GB | fits in fast memory | ~171 tok/s | ollama run lfm2.5-thinking:1.2b-q8_0 |
| M2 Ultra 192GB | Ollama | Q8_0 | 1.9 GB | fits in fast memory | ~533 tok/s | ollama run lfm2.5-thinking:1.2b-q8_0 |
| 2x Mac Studio M5 Max (40c GPU) 128GB | llama.cpp | Q8_0 GGUF | 1.9 GB | fits in fast memory | ~334 tok/s | llama-server -hf unsloth/LFM2.5-1.2B-Thinking-GGUF:Q8_0 --rpc node2:50052 -c 8192 # run rpc-server on each other node |
| Mac Studio M3 Ultra 256GB | Ollama | Q8_0 | 1.9 GB | fits in fast memory | ~546 tok/s | ollama run lfm2.5-thinking:1.2b-q8_0 |
| Mac Studio M5 Ultra (64c GPU) 256GB | Ollama | Q8_0 | 1.9 GB | fits in fast memory | ~800 tok/s | ollama run lfm2.5-thinking:1.2b-q8_0 |
| Mac Studio M5 Ultra (80c GPU) 256GB | Ollama | Q8_0 | 1.9 GB | fits in fast memory | ~800 tok/s | ollama run lfm2.5-thinking:1.2b-q8_0 |
| 2x DGX Spark 128GB | llama.cpp | Q8_0 GGUF | 1.9 GB | fits in fast memory | ~139 tok/s | llama-server -hf unsloth/LFM2.5-1.2B-Thinking-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 | 1.9 GB | fits in fast memory | ~295 tok/s | llama-server -hf unsloth/LFM2.5-1.2B-Thinking-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 | 1.9 GB | fits in fast memory | ~653 tok/s | llama-server -hf unsloth/LFM2.5-1.2B-Thinking-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 | 1.9 GB | fits in fast memory | ~546 tok/s | ollama run lfm2.5-thinking:1.2b-q8_0 |
| 4x DGX Spark 128GB | llama.cpp | Q8_0 GGUF | 1.9 GB | fits in fast memory | ~123 tok/s | llama-server -hf unsloth/LFM2.5-1.2B-Thinking-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 | 1.9 GB | fits in fast memory | ~576 tok/s | llama-server -hf unsloth/LFM2.5-1.2B-Thinking-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