# LFM2.5 (350M)

> Liquid AI's compact LFM2.5 model combines double-gated LIV convolution blocks with periodic GQA layers.

| Property | Value |
| --- | --- |
| Lab | Liquid AI (United States) |
| Released | 2026-05-28 |
| Decoder type | Dense hybrid |
| Family | Dense hybrid |
| Scale | 350M parameters |
| Context window | 128,000 tokens |
| Attention | LIV convolution blocks plus GQA |
| Layer mix | 10 LIV conv + 6 GQA |
| KV cache / token (bf16) | 12 KiB (Very low) |
| License | LFM Open License v1.0 |

**Key detail:** Uses a 16-layer hybrid stack with 10 LIV convolution layers and 6 GQA layers.

## Architecture concepts

- [Grouped-Query Attention (GQA)](https://llm-atlas-7or.pages.dev/concepts/gqa.md): Several query heads share one key/value head, shrinking the KV cache with little quality loss.

## Links

- Architecture diagram: https://sebastianraschka.com/llm-architecture-gallery/images/architectures/lfm2-5-350m.webp
- config.json: https://huggingface.co/LiquidAI/LFM2.5-350M/blob/main/config.json
- License: https://huggingface.co/LiquidAI/LFM2.5-350M/blob/main/LICENSE
- Tech report: https://www.liquid.ai/blog/lfm2-5-350m-no-size-left-behind
- Source card (source of truth): https://sebastianraschka.com/llm-architecture-gallery/#card-lfm2-5-350m
- Web page: https://llm-atlas-7or.pages.dev/models/lfm2-5-350m/
- JSON: https://llm-atlas-7or.pages.dev/api/models/lfm2-5-350m.json

_Data from Sebastian Raschka's LLM Architecture Gallery (https://sebastianraschka.com/llm-architecture-gallery/). Synced 2026-11-04._