AllocateGemma 3n E4B Instruct vs Kimi K2.7 Code
Gemma 3n E4B Instruct is not currently in the Allocate serving catalog, so this page lists no prices for it: every price on this site comes from the live catalog.
Gemma 3n E4B Instruct
Kimi K2.7 CodeLabGoogleMoonshot AI
AccessNot served on AllocateOpen weights
Context windown/a256K tokens
List price, inputNot served$0.95 / M tokens
List price, outputNot served$4 / M tokens
Cached inputn/a$0.19 / M tokens
LicenseNot listedNot listed
Fine-tunableYesYes
Specifications and provider list prices from the Allocate catalog, checked 2026-09-12.
Choose Gemma 3n E4B Instruct for
- Cheap classification
- On-device and edge deployments
- High-volume short prompts
Choose Kimi K2.7 Code for
- Published cached-input pricing ($0.19 per M tokens)
Common questions
Which has the bigger context window?
Kimi K2.7 Code: 262,144 tokens (256K) against an unlisted window for Gemma 3n E4B Instruct.
Can I fine-tune Gemma 3n E4B Instruct or Kimi K2.7 Code?
Both publish open weights (Gemma 3n E4B Instruct: Not listed; Kimi K2.7 Code: Not listed), so both can be fine-tuned. On Allocate the trained weights stay inside your boundary and belong to you.
Related comparisons
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Run the numbers on your workload
Or do not 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.