# Pearl Gemma 4 31B Instruct vs Qwen 3.5

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

| | Pearl Gemma 4 31B Instruct | Qwen 3.5 |
| --- | --- | --- |
| Lab | Pearl AI | Qwen |
| Access | Not served on Allocate | Open weights |
| Context window | n/a | 256K tokens |
| List price, input | Not served | $0.60 / M tokens |
| List price, output | Not served | $3.60 / M tokens |
| Cached input | n/a | $0.35 / M tokens |
| License | Not listed | Apache 2.0 |
| Fine-tunable | Yes | Yes |

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

## Choose Pearl Gemma 4 31B Instruct for

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

## Choose Qwen 3.5 for

- Multilingual support agents
- Translation-adjacent workflows
- Fine-tuning under Apache 2.0

## Common questions

### Which has the bigger context window?

Qwen 3.5: 262,144 tokens (256K) against an unlisted window for Pearl Gemma 4 31B Instruct.

### Can I fine-tune Pearl Gemma 4 31B Instruct or Qwen 3.5?

Both publish open weights (Pearl Gemma 4 31B Instruct: Not listed; Qwen 3.5: Apache 2.0), 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/pearl-gemma-4-31b-it-vs-qwen-3-5) · [Pearl Gemma 4 31B Instruct](https://allocate.network/models/pearl-gemma-4-31b-it.md) · [Qwen 3.5](https://allocate.network/models/qwen-3-5.md) · [Machine-readable catalog](https://allocate.network/catalog.json)