Model benchmarks

unsloth/LFM2.5-1.2B-Thinking-GGUF local LLM performance

As of September 2026, unsloth/LFM2.5-1.2B-Thinking-GGUF runs at up to 335.4 tok/s for local inference (best of 9 community benchmark runs across 2 GPUs).

Unsloth Studiollama.cppQ4_K_M
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Model size

1.2B

Peak speed

335.4 tok/s

Average speed

293.5 tok/s

Avg PP

1294.6 tok/s

Min memory

n/a

Max context

128,000 tokens

Avg output / run

14,726 tokens

Avg runtime / run

1m 9s

Avg quality

30.4

Benchmark runs

9

GPUs tested

2

Quality by task

Average LLM-judged quality (0–100) with the run-to-run spread shown as a P5–P95 band, overall and for each benchmark task, across all 9 runs. The low and high columns show how much the judge’s score varies between runs, and need at least two runs to display.

TaskP5 (low)AvgP95 (high)
Overall25.530.436.3
Agent Workflow26.541.059.4
Code Generation3.57.712.9
Role Play & Narrative33.648.960.1
Research & Analysis14.724.035.2

Performance by hardware and tool

Every hardware/tool/quantization combination unsloth/LFM2.5-1.2B-Thinking-GGUF has been benchmarked on, ranked by peak token generation speed. Last updated September 2026.

HardwareToolQuantBest tok/sAvg tok/sMemoryContextQualityRuns
NVIDIA GeForce RTX 4070Unsloth StudioQ4_K_M335.4 tok/s335.4 tok/sn/a65,536 tokens31.81
NVIDIA GeForce RTX 4070llama.cpp—332.8 tok/s319.5 tok/sn/a128,000 tokens31.17
Intel(R) Arc(TM) 140V GPU (16GB)Unsloth Studio—69.8 tok/s69.8 tok/sn/a128,000 tokens24.01

Benchmark runs

All 9 unsloth/LFM2.5-1.2B-Thinking-GGUF runs submitted so far — expand one for its hardware, quality breakdown and per-scenario detail.

Frequently asked questions

How fast is unsloth/LFM2.5-1.2B-Thinking-GGUF for local inference?
Across 9 community benchmark runs, unsloth/LFM2.5-1.2B-Thinking-GGUF reaches up to 335.4 tok/s and averages 293.5 tok/s, with the fastest results on NVIDIA GeForce RTX 4070.
Which tools have been used to run unsloth/LFM2.5-1.2B-Thinking-GGUF?
Benchmarks were submitted using Unsloth Studio, llama.cpp. Results are community-contributed and updated as new runs arrive.