# Pearl-ai Gemma-4-31B-it-pearl vs GLM 4.5 Air

On provider list prices, GLM 4.5 Air costs $0.13 per million input tokens against $0.28 for Pearl-ai Gemma-4-31B-it-pearl: 2.2x apart. Output is $0.85 against $0.86.

## Specifications

| | Pearl-ai Gemma-4-31B-it-pearl | GLM 4.5 Air |
| --- | --- | --- |
| Lab | pearl.ai | Z.ai |
| Access | Open weights | Open weights |
| Context window | 256K tokens | 128K tokens |
| List price, input | $0.28 / M tokens | $0.13 / M tokens |
| List price, output | $0.86 / M tokens | $0.85 / M tokens |
| Cached input | n/a | $0.025 / M tokens |
| License | Not listed | MIT |
| Fine-tunable | Yes | Yes |

Specifications and provider list prices from the Allocate catalog, checked 2026-07-21.

## What the numbers say

Take 1,000,000 requests a month at 1,200 input and 350 output tokens each. That workload costs $453.50 a month on GLM 4.5 Air and $637 on Pearl-ai Gemma-4-31B-it-pearl at list: a gap of $183.50, or 1.4x.

Pearl-ai Gemma-4-31B-it-pearl reads 256K tokens per request against 128K for GLM 4.5 Air, 2.0x the window. That decides which one can take whole documents without splitting them.

## Choose Pearl-ai Gemma-4-31B-it-pearl for

- The longer context window (256K vs 128K tokens)

## Choose GLM 4.5 Air for

- The lower list price ($0.13 in / $0.85 out per M tokens)
- Fine-tuning under a permissive license (MIT)
- Published cached-input pricing ($0.025 per M tokens)

## Common questions

### Which is cheaper, Pearl-ai Gemma-4-31B-it-pearl or GLM 4.5 Air?

GLM 4.5 Air, on this workload shape. At list prices it is $0.13/$0.85 per million tokens in and out against $0.28/$0.86 for Pearl-ai Gemma-4-31B-it-pearl. Billed on Allocate: $0.14/$0.91 against $0.30/$0.92.

### Which has the bigger context window?

Pearl-ai Gemma-4-31B-it-pearl: 262,144 tokens (256K) against 131,072 (128K) for GLM 4.5 Air.

### Can I fine-tune Pearl-ai Gemma-4-31B-it-pearl or GLM 4.5 Air?

Both publish open weights (Pearl-ai Gemma-4-31B-it-pearl: Not listed; GLM 4.5 Air: MIT), 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-z-ai-glm-4-5-air) · [Pearl-ai Gemma-4-31B-it-pearl](https://allocate.network/models/pearl-gemma-4-31b-it.md) · [GLM 4.5 Air](https://allocate.network/models/z-ai-glm-4-5-air.md) · [Machine-readable catalog](https://allocate.network/catalog.json)