llamaperf

LFM2.5 2.6B

on M1 8GB · llama.cpp · 32,000 ctx

Tone: positiveApple hardware
Oct 4, 2026
Throughput
22.0 t/s gen · 200.0 tokens/s prompt processing (prefill)Prompt processing measures input prefill speed; it does not tell you the time to first token.
Quant
QAD-Q4_0 (GGUF)

Use cases

agentictool-use

Summary

User compares LFM2.5 2.6B and MiniCPM5 2B on small agentic tool-use tasks on an M1 Air. LFM2.5 2.6B runs at 200 t/s prompt and 22 t/s generation with llama.cpp, QAD-Q4_0 GGUF, 32k context, using about 2.5 GB of RAM. MiniCPM5 2B runs at 162 t/s prompt and 16 t/s generation with a DSpark draft model, Q8_0 GGUF, 32k context, q5_1 KV cache, using about 3.8 GB of RAM. User calls LFM2.5 the clear winner: faster, less RAM despite more parameters, and better aligned for English conversation. MiniCPM5 is noted as often responding in Chinese and hallucinating less, but LFM2.5 tends to hallucinate as conversations get longer.