Yes — LFM2.5-2.6B (2.6B) runs at 220 tok/s on M5 Max with 64 GB RAM using Q4_K_M quantization via MLX. First token latency is 0.1s. A capable open-source LLM with 2.6B parameters.
Want to run LFM2.5-2.6B faster — or step up to bigger models? Find your Mac →The LLMCheck index estimates LFM2.5-2.6B on M5 Max using our published methodology: Q4_K_M quantization, memory-bandwidth scaling, and cross-referenced third-party benchmarks where available. Figures are transparent estimates — own this config? Submit a real benchmark →
| Metric | Value |
|---|---|
| Tokens per second | 220 tok/s |
| Time to first token | 0.1s |
| Quantization | Q4_K_M |
| Minimum RAM | 64 GB |
| Recommended engine | MLX |
| Parameters | 2.6B |
| Benchmark date | 2026-08 |
Q4_K_M 2.6B MLX M5 Max
The recommended engine for LFM2.5-2.6B on M5 Max is MLX. Install with pip and pull the model:
Alternatively, you can use Ollama for a simpler setup:
To run LFM2.5-2.6B on M5 Max you need:
LFM2.5-2.6B needs about 64 GB of unified memory. These current Apple Silicon Macs have the headroom to run it comfortably:
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See how LFM2.5-2.6B stacks up against other models on your specific Mac hardware.
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