# Kimi K2.7 Code vs Pearl Gemma 4 31B Instruct

Pearl Gemma 4 31B 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.

## Specifications

| | Kimi K2.7 Code | Pearl Gemma 4 31B Instruct |
| --- | --- | --- |
| Lab | Moonshot AI | Pearl AI |
| Access | Open weights | Not served on Allocate |
| Context window | 256K tokens | n/a |
| List price, input | $0.95 / M tokens | Not served |
| List price, output | $4 / M tokens | Not served |
| Cached input | $0.19 / M tokens | 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 Kimi K2.7 Code for

- Published cached-input pricing ($0.19 per M tokens)

## Choose Pearl Gemma 4 31B Instruct for

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

## Common questions

### Which has the bigger context window?

Kimi K2.7 Code: 262,144 tokens (256K) against an unlisted window for Pearl Gemma 4 31B Instruct.

### Can I fine-tune Kimi K2.7 Code or Pearl Gemma 4 31B Instruct?

Both publish open weights (Kimi K2.7 Code: 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/moonshotai-kimi-k2-7-code-vs-pearl-gemma-4-31b-it) · [Kimi K2.7 Code](https://allocate.network/models/moonshotai-kimi-k2-7-code.md) · [Pearl Gemma 4 31B Instruct](https://allocate.network/models/pearl-gemma-4-31b-it.md) · [Machine-readable catalog](https://allocate.network/catalog.json)