DiggTop ⌕

LFM2.5-2.6B

Llama family · 3.0B params

2recorded runs
305.6best tok/s
2verified

Evidence: 2 sourced runs · 1 independent source · first recorded Aug 26, 2026 · last recorded Sep 4, 2026. What these labels mean.

What the LFM2.5-2.6B numbers mean

The fastest verified result on our board is 305.6 output tok/s on an RTX 3090 at Q4_K_M with a 24576-token context. That is about 3.3 ms per generated token — 500 tokens takes roughly 1.6 seconds. Prompt processing on the same record runs at 7609.8 tok/s, so a 2,000-token prompt is read in about 0.3 seconds. Peak VRAM was measured at 2.3 GB. Across the 2 records we hold for this model the range is 132.4–305.6 tok/s on 2 GPUs, because quantisation, context length and the engine build all move the number.

How much VRAM does LFM2.5-2.6B need?

LFM2.5-2.6B has 3.0B parameters. These estimates use the same formula as the VRAM calculator: weights, plus about 15% for a moderate-context KV cache and runtime overhead, plus a small engine floor.

QuantisationEstimated VRAMSmallest card that fits
Q4_K_M (4-bit)2.7 GB8 GB
Q8_0 (8-bit)4.5 GB8 GB
FP16 (16-bit)7.7 GB12 GB

Long contexts and large batches raise the real number — read the smallest card as "possible with a reduced context". Measured throughput is on the benchmark board.

Fastest GPUs for this model (best tok/s)
  1. RTX 3090305.6
  2. Intel Arc Pro B70132.4

Models with a similar footprint

ModelParamsQ4_K_M weights
Llama-3.2-3B-Instruct3B1.7 GB
Ministral-3-3B-Instruct-25123B1.7 GB
OpenLLaMA-3B3B1.7 GB
VibeThinker-3B3B1.7 GB
gemma-3n-E4B-it-text4B2.2 GB
NVIDIA-Nemotron-3-Nano-4B4B2.2 GB

Ranked by distance from LFM2.5-2.6B's parameter count. Full benchmark board.

All benchmarks Methodology

GPUModelQuantBackendCtx tok/sprompt tok/sVRAM GBSource
RTX 3090 · 24 GBLFM2.5-2.6BQ4_K_Mllama.cpp 0.3.0-dev (build 1, commit d7bd3bf)24576305.6 ✓7609.82.3src
Intel Arc Pro B70 · 32 GBLFM2.5-2.6BQ8_0llama.cpp 9fee29e9435f; oneAPI 2026.1.18192132.4 ✓——src
↑