LFM2.5-230M-GGUF
LFM2 is a new generation of hybrid models developed by Liquid AI, specifically designed for edge AI and on-device deployment. It sets a new standard in terms of quality, speed, and memory efficiency.
Params
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Context
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Downloads 30d
586 K
Likes
104
Download history
daily snapshots · 28 days597 K180 K
Aug 25Sep 3Sep 12Sep 21
Can you run it?
Estimated VRAM at 8K context unless noted. Pick your hardware to see the verdict per quantization.
| File | Quant | Size | Est. VRAM | Verdict on RTX 4090 · 24 GB |
|---|---|---|---|---|
| LFM2.5-230M-QAD-Q4_0.gguf | Q4_0 | 0.1 GB | 0.7 GB | ✅ Runs comfortably |
| LFM2.5-230M-Q4_K_M.gguf | Q4_K_M | 0.2 GB | 0.7 GB | ✅ Runs comfortably |
| LFM2.5-230M-Q5_K_M.gguf | Q5_K_M | 0.2 GB | 0.7 GB | ✅ Runs comfortably |
| LFM2.5-230M-Q6_K.gguf | Q6_K | 0.2 GB | 0.7 GB | ✅ Runs comfortably |
| LFM2.5-230M-Q8_0.gguf | Q8_0 | 0.2 GB | 0.8 GB | ✅ Runs comfortably |
| LFM2.5-230M-BF16.gguf | GGUF | 0.5 GB | 1.0 GB | ✅ Runs comfortably |
Estimate: file size × 1.1 + KV cache at 8K + 0.5 GB overhead. Not a benchmark — how we calculate this.
Run it
copy-paste, exact tags checked against the Hub$ ollama run lfm2-5-230m-gguf # pin the quantization explicitly $ ollama run lfm2-5-230m-gguf-q4_0
$ huggingface-cli download LiquidAI/LFM2.5-230M-GGUF-GGUF \
LFM2.5-230M-QAD-Q4_0.gguf --local-dir .
$ llama-cli -m LFM2.5-230M-QAD-Q4_0.gguf \
-c 8192 -ngl 99 -t 8 --color
$ curl -s https://aimodelscomparison.com/api/v1/models/lfm2-5-230m-gguf
{
"hf_id": "LiquidAI/LFM2.5-230M-GGUF",
"params_b": null,
"context_length": null,
"license": { "id": "other", "commercial": "unknown" },
"downloads_30d": 585535,
"vram_estimates": [
{ "quant": "GGUF", "gb": 1.0 },
{ "quant": "Q4_0", "gb": 0.7 }
],
"updated_at": "2026-08-25T01:01:17Z"
}
Specifications
- Licence
- other
- First seen on the Hub
- 2026-06-11
- Training datasets
- undisclosed
- Added to our catalog
- 2026-08-25
Compare with any text-generation model