# Gemma 3N E4B Instruct vs LFM2.5-8B-A1B

On provider list prices, LFM2.5-8B-A1B costs $0.03 per million input tokens against $0.06 for Gemma 3N E4B Instruct: 2.0x apart. Output is $0.12 against $0.12. On Allocate both bill at list plus the 7% transaction fee.

## Specifications

| | Gemma 3N E4B Instruct | LFM2.5-8B-A1B |
| --- | --- | --- |
| Lab | Google | LiquidAI |
| Access | Open weights | Open weights |
| Context window | 32K tokens | 32K tokens |
| List price, input | $0.06 / M tokens | $0.03 / M tokens |
| List price, output | $0.12 / M tokens | $0.12 / M tokens |
| Cached input | n/a | n/a |
| License | Gemma terms | Custom license |
| Fine-tunable | Yes | Yes |

Specifications and provider list prices from the Allocate catalog, checked 2026-07-08. Billed price is list plus the 7% transaction fee.

## What the numbers say

Take 1,000,000 requests a month at 1,200 input and 350 output tokens each. That workload costs $78 a month on LFM2.5-8B-A1B and $114 on Gemma 3N E4B Instruct at list: a gap of $36, or 1.5x.

## Choose Gemma 3N E4B Instruct for

- Training toward a model you own

## Choose LFM2.5-8B-A1B for

- The lower list price ($0.03 in / $0.12 out per M tokens)

## Common questions

### Which is cheaper, Gemma 3N E4B Instruct or LFM2.5-8B-A1B?

LFM2.5-8B-A1B, on this workload shape. At list prices it is $0.03/$0.12 per million tokens in and out against $0.06/$0.12 for Gemma 3N E4B Instruct. Billed on Allocate: $0.032/$0.13 against $0.064/$0.13, list plus 7%.

### Which has the bigger context window?

They match: both read 32,768 tokens (32K) per request.

### Can I fine-tune Gemma 3N E4B Instruct or LFM2.5-8B-A1B?

Both publish open weights (Gemma 3N E4B Instruct: Gemma terms; LFM2.5-8B-A1B: Custom license), 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/google-gemma-3n-e4b-it-vs-liquid-lfm2-5-8b-a1b) · [Gemma 3N E4B Instruct](https://allocate.network/models/google-gemma-3n-e4b-it.md) · [LFM2.5-8B-A1B](https://allocate.network/models/liquid-lfm2-5-8b-a1b.md) · [Machine-readable catalog](https://allocate.network/catalog.json)