Model benchmarks
LiquidAI/LFM2.5-350M-GGUF:F16 local LLM performance
As of August 2026, LiquidAI/LFM2.5-350M-GGUF:F16 runs at up to 665.0 tok/s for local inference (best of 2 community benchmark runs across 1 GPU).
Model size
Unknown
Peak speed
665.0 tok/s
Average speed
635.1 tok/s
Min memory
3.4 GB
Max context
65,536 tokens
Avg output / run
3,395 tokens
Avg runtime / run
5s
Avg quality
17.4
Benchmark runs
2
GPUs tested
1
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 2 runs. The low and high columns show how much the judge’s score varies between runs, and need at least two runs to display.
| Task | P5 (low) | Avg | P95 (high) |
|---|---|---|---|
| Overall | 15.7 | 17.4 | 19.0 |
| Agent Workflow | 17.9 | 24.1 | 30.3 |
| Code Generation | 2.6 | 3.5 | 4.4 |
| Role Play & Narrative | 24.8 | 25.7 | 26.6 |
| Research & Analysis | 13.9 | 16.2 | 18.4 |
Performance by hardware and tool
Every hardware/tool/quantization combination LiquidAI/LFM2.5-350M-GGUF:F16 has been benchmarked on, ranked by peak token generation speed. Last updated August 2026.
| Hardware | Tool | Quant | Best tok/s | Avg tok/s | Memory | Context | Quality | Runs |
|---|---|---|---|---|---|---|---|---|
| NVIDIA GeForce RTX 3080 Ti | llama.cpp | — | 665.0 tok/s | 635.1 tok/s | 3.4 GB | 65,536 tokens | 17.4 | 2 |
Frequently asked questions
- How fast is LiquidAI/LFM2.5-350M-GGUF:F16 for local inference?
- Across 2 community benchmark runs, LiquidAI/LFM2.5-350M-GGUF:F16 reaches up to 665.0 tok/s and averages 635.1 tok/s, with the fastest results on NVIDIA GeForce RTX 3080 Ti.
- How much memory does LiquidAI/LFM2.5-350M-GGUF:F16 need?
- The leanest observed configuration used about 3.4 GB of memory.
- Which tools have been used to run LiquidAI/LFM2.5-350M-GGUF:F16?
- Benchmarks were submitted using llama.cpp. Results are community-contributed and updated as new runs arrive.