Comparisons

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.

Gemma 3N E4B InstructL LFM2.5-8B-A1B
LabGoogleLiquidAI
AccessOpen weightsOpen weights
Context window32K tokens32K tokens
List price, input$0.06 / M tokens$0.03 / M tokens
List price, output$0.12 / M tokens$0.12 / M tokens
Cached inputn/an/a
LicenseGemma termsCustom license
Fine-tunableYesYes

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.

LFM2.5-8B-A1B$0.03$0.12
Gemma 3N E4B Instruct$0.06$0.12
InputOutput

Choose Gemma 3N E4B Instruct for

  • Training toward a model you own
Gemma 3N E4B Instruct details

Choose LFM2.5-8B-A1B for

  • The lower list price ($0.03 in / $0.12 out per M tokens)
LFM2.5-8B-A1B details

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.

Related comparisons

Run the numbers on your workload

Or don’t choose. On Allocate a route name is the contract: point yours at one model today, swap to the other tomorrow, and compare them on your live traffic with per-token metering.