# LFM2.5 8B A1B vs Pearl Gemma 4 31B Instruct

LFM2.5 8B A1B and Pearl Gemma 4 31B Instruct are not currently in the Allocate serving catalog, so this page lists no prices for them: every price on this site comes from the live catalog.

## Specifications

| | LFM2.5 8B A1B | Pearl Gemma 4 31B Instruct |
| --- | --- | --- |
| Lab | Liquid AI | Pearl AI |
| Access | Not served on Allocate | Not served on Allocate |
| Context window | n/a | n/a |
| List price, input | Not served | Not served |
| List price, output | Not served | Not served |
| Cached input | n/a | n/a |
| License | Not listed | Not listed |
| Fine-tunable | Yes | Yes |

Specifications and provider list prices from the Allocate catalog, checked 2026-09-12.

## Choose LFM2.5 8B A1B for

- High-volume extraction
- Latency-sensitive routes
- Edge deployments

## Choose Pearl Gemma 4 31B Instruct for

- Long-document reasoning
- Open-weight fine-tuning
- Mid-size general work

## Common questions

### Can I fine-tune LFM2.5 8B A1B or Pearl Gemma 4 31B Instruct?

Both publish open weights (LFM2.5 8B A1B: Not listed; Pearl Gemma 4 31B Instruct: Not listed), so both can be fine-tuned. On Allocate the trained weights stay inside your boundary and belong to you.

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[HTML page](https://allocate.network/compare/liquid-lfm2-5-8b-a1b-vs-pearl-gemma-4-31b-it) · [LFM2.5 8B A1B](https://allocate.network/models/liquid-lfm2-5-8b-a1b.md) · [Pearl Gemma 4 31B Instruct](https://allocate.network/models/pearl-gemma-4-31b-it.md) · [Machine-readable catalog](https://allocate.network/catalog.json)