REDDIT · REDDIT// 3d agoBENCHMARK RESULT

Liquid AI’s LFM2.5 Q8 flies on aging CPUs

The post highlights a benchmark-style result for Liquid AI’s LFM2.5-1.2B-Instruct in a Q8 quantized local run, with the screenshot claiming 109.9 tokens per second on a six-year-old PC. That lines up with Liquid AI’s broader positioning for LFM2.5 as a compact, on-device model family built for fast inference and low memory use, especially in CPU and edge deployments.

// ANALYSIS

Hot take: this is less about raw model intelligence and more about how aggressively Liquid AI has optimized the stack for local inference, and that is the real story.

–The reported speed is the headline: 109.9 t/s on older desktop hardware is strong enough to make the model interesting for local-first users.
–The result fits Liquid AI’s published pitch for LFM2.5 as a fast, sub-2B on-device model family with quantized deployment options.
–Because this is a Reddit screenshot rather than a formal benchmark report, treat the exact number as anecdotal unless replicated on the same hardware/config.
–For enthusiasts, the practical signal is that Q8 quantization can preserve enough quality while staying very fast on consumer CPUs.

// TAGS

lfm2.5liquid-ailocal-llmquantizationq8cpu-inferenceon-device-aillama-cpp

DISCOVERED

3d ago

2026-04-09

PUBLISHED

3d ago

2026-04-09

RELEVANCE

8/ 10

AUTHOR

reg-kdeneonuser