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Liquid AI · 8.47B parameters (1B active) · chat, reasoning, coding.
Ollama weight files: Q4_K_M 5.2 GB (lfm2.5:8b); Q8_0 9 GB (lfm2.5:8b-a1b-q8_0).
Yes on 59 machines in this list. The smallest is RTX 3060 Ti 8GB: Q4_K_M, about 6 GB, roughly 219 tokens per second, via Ollama. ollama run lfm2.5:8b
ollama run lfm2.5:8b-a1b-q8_0ollama run lfm2.5:8b-a1b-q8_0ollama run lfm2.5:8b-a1b-q8_0ollama run lfm2.5:8b-a1b-q8_0lms get unsloth/LFM2.5-8B-A1B-GGUF@Q8_0llama-server -hf unsloth/LFM2.5-8B-A1B-GGUF:Q8_0 -c 8192vllm serve LiquidAI/LFM2.5-8B-A1B --max-model-len 8192 --gpu-memory-utilization 0.9| Hardware | Runtime | Quant | Memory | Fit | Speed | Command |
|---|---|---|---|---|---|---|
| RTX 3060 Ti 8GB | Ollama | Q4_K_M | 6 GB | fits in fast memory | ~219 tok/s | ollama run lfm2.5:8b |
| RTX 3070 8GB | Ollama | Q4_K_M | 6 GB | fits in fast memory | ~219 tok/s | ollama run lfm2.5:8b |
| RTX 4060 8GB | Ollama | Q4_K_M | 6 GB | fits in fast memory | ~133 tok/s | ollama run lfm2.5:8b |
| RX 7600 8GB | Ollama | Q4_K_M | 6 GB | fits in fast memory | ~141 tok/s | ollama run lfm2.5:8b |
| RTX 3080 10GB | Ollama | Q4_K_M | 6 GB | fits in fast memory | ~371 tok/s | ollama run lfm2.5:8b |
| M1 16GB | Ollama | Q8_0 | 9.8 GB | fits in fast memory | ~26 tok/s | ollama run lfm2.5:8b-a1b-q8_0 |
| M2 16GB | Ollama | Q8_0 | 9.8 GB | fits in fast memory | ~38 tok/s | ollama run lfm2.5:8b-a1b-q8_0 |
| M3 16GB | Ollama | Q8_0 | 9.8 GB | fits in fast memory | ~38 tok/s | ollama run lfm2.5:8b-a1b-q8_0 |
| M4 16GB | Ollama | Q8_0 | 9.8 GB | fits in fast memory | ~45 tok/s | ollama run lfm2.5:8b-a1b-q8_0 |
| RTX 3060 12GB | Ollama | Q8_0 | 9.8 GB | fits in fast memory | ~102 tok/s | ollama run lfm2.5:8b-a1b-q8_0 |
| RTX 4070 12GB | Ollama | Q8_0 | 9.8 GB | fits in fast memory | ~142 tok/s | ollama run lfm2.5:8b-a1b-q8_0 |
| RTX 5070 12GB | Ollama | Q8_0 | 9.8 GB | fits in fast memory | ~190 tok/s | ollama run lfm2.5:8b-a1b-q8_0 |
| RTX 4060 Ti 16GB | Ollama | Q8_0 | 9.8 GB | fits in fast memory | ~81 tok/s | ollama run lfm2.5:8b-a1b-q8_0 |
| RTX 4070 Ti Super 16GB | Ollama | Q8_0 | 9.8 GB | fits in fast memory | ~190 tok/s | ollama run lfm2.5:8b-a1b-q8_0 |
| RTX 4080 16GB | Ollama | Q8_0 | 9.8 GB | fits in fast memory | ~202 tok/s | ollama run lfm2.5:8b-a1b-q8_0 |
| RTX 5080 16GB | Ollama | Q8_0 | 9.8 GB | fits in fast memory | ~271 tok/s | ollama run lfm2.5:8b-a1b-q8_0 |
| RX 7800 XT 16GB | Ollama | Q8_0 | 9.8 GB | fits in fast memory | ~176 tok/s | ollama run lfm2.5:8b-a1b-q8_0 |
| RX 9070 XT 16GB | Ollama | Q8_0 | 9.8 GB | fits in fast memory | ~181 tok/s | ollama run lfm2.5:8b-a1b-q8_0 |
| M2 24GB | Ollama | Q8_0 | 9.8 GB | fits in fast memory | ~38 tok/s | ollama run lfm2.5:8b-a1b-q8_0 |
| M3 24GB | Ollama | Q8_0 | 9.8 GB | fits in fast memory | ~38 tok/s | ollama run lfm2.5:8b-a1b-q8_0 |
| M4 24GB | Ollama | Q8_0 | 9.8 GB | fits in fast memory | ~45 tok/s | ollama run lfm2.5:8b-a1b-q8_0 |
| RTX 3090 24GB | Ollama | Q8_0 | 9.8 GB | fits in fast memory | ~264 tok/s | ollama run lfm2.5:8b-a1b-q8_0 |
| RTX 4090 24GB | Ollama | Q8_0 | 9.8 GB | fits in fast memory | ~285 tok/s | ollama run lfm2.5:8b-a1b-q8_0 |
| RX 7900 XTX 24GB | Ollama | Q8_0 | 9.8 GB | fits in fast memory | ~271 tok/s | ollama run lfm2.5:8b-a1b-q8_0 |
| M1 Pro 32GB | Ollama | Q8_0 | 9.8 GB | fits in fast memory | ~75 tok/s | ollama run lfm2.5:8b-a1b-q8_0 |
| M2 Pro 32GB | Ollama | Q8_0 | 9.8 GB | fits in fast memory | ~75 tok/s | ollama run lfm2.5:8b-a1b-q8_0 |
| M4 32GB | Ollama | Q8_0 | 9.8 GB | fits in fast memory | ~45 tok/s | ollama run lfm2.5:8b-a1b-q8_0 |
| M3 Pro 36GB | Ollama | Q8_0 | 9.8 GB | fits in fast memory | ~56 tok/s | ollama run lfm2.5:8b-a1b-q8_0 |
| Mac Studio M4 Max (32c GPU) 36GB | Ollama | Q8_0 | 9.8 GB | fits in fast memory | ~154 tok/s | ollama run lfm2.5:8b-a1b-q8_0 |
| Mac Studio M5 Max (32c GPU) 36GB | Ollama | Q8_0 | 9.8 GB | fits in fast memory | ~173 tok/s | ollama run lfm2.5:8b-a1b-q8_0 |
| RTX 5090 32GB | Ollama | Q8_0 | 9.8 GB | fits in fast memory | ~506 tok/s | ollama run lfm2.5:8b-a1b-q8_0 |
| M4 Pro 48GB | Ollama | Q8_0 | 9.8 GB | fits in fast memory | ~103 tok/s | ollama run lfm2.5:8b-a1b-q8_0 |
| Mac Studio M4 Max (40c GPU) 48GB | Ollama | Q8_0 | 9.8 GB | fits in fast memory | ~206 tok/s | ollama run lfm2.5:8b-a1b-q8_0 |
| Mac Studio M5 Max (40c GPU) 48GB | Ollama | Q8_0 | 9.8 GB | fits in fast memory | ~231 tok/s | ollama run lfm2.5:8b-a1b-q8_0 |
| M1 Max 64GB | Ollama | Q8_0 | 9.8 GB | fits in fast memory | ~151 tok/s | ollama run lfm2.5:8b-a1b-q8_0 |
| M2 Max 64GB | Ollama | Q8_0 | 9.8 GB | fits in fast memory | ~151 tok/s | ollama run lfm2.5:8b-a1b-q8_0 |
| M3 Max 64GB | Ollama | Q8_0 | 9.8 GB | fits in fast memory | ~151 tok/s | ollama run lfm2.5:8b-a1b-q8_0 |
| M4 Max 64GB | Ollama | Q8_0 | 9.8 GB | fits in fast memory | ~206 tok/s | ollama run lfm2.5:8b-a1b-q8_0 |
| Mac Studio M4 Max (40c GPU) 64GB | Ollama | Q8_0 | 9.8 GB | fits in fast memory | ~206 tok/s | ollama run lfm2.5:8b-a1b-q8_0 |
| Mac Studio M5 Max (40c GPU) 64GB | Ollama | Q8_0 | 9.8 GB | fits in fast memory | ~231 tok/s | ollama run lfm2.5:8b-a1b-q8_0 |
| DGX Spark 64GB (ASUS, Dell, HP, MSI, Acer, Gigabyte) | Ollama | Q8_0 | 9.8 GB | fits in fast memory | ~148 tok/s | ollama run lfm2.5:8b-a1b-q8_0 |
| Mac Studio M3 Ultra 96GB | Ollama | Q8_0 | 9.8 GB | fits in fast memory | ~308 tok/s | ollama run lfm2.5:8b-a1b-q8_0 |
| Mac Studio M5 Ultra 96GB | Ollama | Q8_0 | 9.8 GB | fits in fast memory | ~452 tok/s | ollama run lfm2.5:8b-a1b-q8_0 |
| M3 Max 128GB | Ollama | Q8_0 | 9.8 GB | fits in fast memory | ~151 tok/s | ollama run lfm2.5:8b-a1b-q8_0 |
| M4 Max 128GB | Ollama | Q8_0 | 9.8 GB | fits in fast memory | ~206 tok/s | ollama run lfm2.5:8b-a1b-q8_0 |
| Mac Studio M4 Max (40c GPU) 128GB | Ollama | Q8_0 | 9.8 GB | fits in fast memory | ~206 tok/s | ollama run lfm2.5:8b-a1b-q8_0 |
| Mac Studio M5 Max (40c GPU) 128GB | Ollama | Q8_0 | 9.8 GB | fits in fast memory | ~231 tok/s | ollama run lfm2.5:8b-a1b-q8_0 |
| DGX Spark 128GB (NVIDIA, ASUS, Dell, Lenovo, HP, MSI, Acer, Gigabyte) | Ollama | Q8_0 | 9.8 GB | fits in fast memory | ~148 tok/s | ollama run lfm2.5:8b-a1b-q8_0 |
| M2 Ultra 192GB | Ollama | Q8_0 | 9.8 GB | fits in fast memory | ~301 tok/s | ollama run lfm2.5:8b-a1b-q8_0 |
| 2x Mac Studio M5 Max (40c GPU) 128GB | llama.cpp | Q8_0 GGUF | 9.8 GB | fits in fast memory | ~196 tok/s | llama-server -hf unsloth/LFM2.5-8B-A1B-GGUF:Q8_0 --rpc node2:50052 -c 8192 # run rpc-server on each other node |
| Mac Studio M3 Ultra 256GB | Ollama | Q8_0 | 9.8 GB | fits in fast memory | ~308 tok/s | ollama run lfm2.5:8b-a1b-q8_0 |
| Mac Studio M5 Ultra (64c GPU) 256GB | Ollama | Q8_0 | 9.8 GB | fits in fast memory | ~452 tok/s | ollama run lfm2.5:8b-a1b-q8_0 |
| Mac Studio M5 Ultra (80c GPU) 256GB | Ollama | Q8_0 | 9.8 GB | fits in fast memory | ~452 tok/s | ollama run lfm2.5:8b-a1b-q8_0 |
| 2x DGX Spark 128GB | llama.cpp | Q8_0 GGUF | 9.8 GB | fits in fast memory | ~125 tok/s | llama-server -hf unsloth/LFM2.5-8B-A1B-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 | 9.8 GB | fits in fast memory | ~173 tok/s | llama-server -hf unsloth/LFM2.5-8B-A1B-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 | 9.8 GB | fits in fast memory | ~384 tok/s | llama-server -hf unsloth/LFM2.5-8B-A1B-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 | 9.8 GB | fits in fast memory | ~308 tok/s | ollama run lfm2.5:8b-a1b-q8_0 |
| 4x DGX Spark 128GB | llama.cpp | Q8_0 GGUF | 9.8 GB | fits in fast memory | ~111 tok/s | llama-server -hf unsloth/LFM2.5-8B-A1B-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 | 9.8 GB | fits in fast memory | ~338 tok/s | llama-server -hf unsloth/LFM2.5-8B-A1B-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