llamaperf

LFM3 1.7B

on NVIDIA RTX 3060 Laptop 6GB · Magnitude

Tone: mixedNVIDIA hardware
Oct 29, 2026
Throughput
91.3 t/s gen · 5257.7 tokens/s prompt processing (prefill)Prompt processing measures input prefill speed; it does not tell you the time to first token.
Quant
Q8 (GGUF)
System RAM
24 GB
VRAM reported
6 GB

Use cases

coding

Summary

User benchmarks LFM3-1.7B Q8 in Magnitude against llama.cpp on an RTX 3060 Laptop 6GB, getting 91.26 t/s generation and 5257.71 t/s prompt processing with Magnitude versus 112.29 t/s and 5710.16 t/s with llama.cpp. Setup is Magnitude's own Rust/TypeScript engine with the Q8 GGUF, benchmarked with llama-benchy at pp2048/tg512; llama.cpp was run via llama-server with only -m set. On a Raspberry Pi 5 CPU-only run at pp128/tg128, Magnitude reached 3.59 t/s generation and 5.07 t/s prompt against llama.cpp's 5.25 and 31.42 t/s. The user could not confirm the claimed 2x speedup, notes Magnitude cannot do partial CPU offload, and says it overestimated VRAM use at 5.3GB when about 4.2GB was reserved.