# GLM 5.2 vs GLM 5.3

On provider list prices, GLM 5.2 costs $1.40 per million input tokens against $1.40 for GLM 5.3: effectively level. Output is $4.40 against $4.40.

## Specifications

| | GLM 5.2 | GLM 5.3 |
| --- | --- | --- |
| Lab | Z.ai | Z.ai |
| Access | Open weights | Open weights |
| Context window | 1M tokens | 1M tokens |
| List price, input | $1.40 / M tokens | $1.40 / M tokens |
| List price, output | $4.40 / M tokens | $4.40 / M tokens |
| Cached input | $0.26 / M tokens | $0.26 / M tokens |
| License | Not listed | Not listed |
| Fine-tunable | Yes | Yes |

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

## What the numbers say

Take 1,000,000 requests a month at 1,200 input and 350 output tokens each. That workload costs $3,220 a month on GLM 5.2 and $3,220 on GLM 5.3 at list: a gap of $0.

## Choose GLM 5.2 for

- Agents on open weights
- Code and structured outputs
- Fine-tuning toward an owned model

## Choose GLM 5.3 for

- Training toward a model you own

## Common questions

### Which is cheaper, GLM 5.2 or GLM 5.3?

GLM 5.2, on this workload shape. At list prices it is $1.40/$4.40 per million tokens in and out against $1.40/$4.40 for GLM 5.3. Billed on Allocate: $1.50/$4.71 against $1.50/$4.71.

### Which has the bigger context window?

They match: both read 1,048,575 tokens (1M) per request.

### Can I fine-tune GLM 5.2 or GLM 5.3?

Both publish open weights (GLM 5.2: Not listed; GLM 5.3: 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/z-ai-glm-5-2-vs-z-ai-glm-5-3) · [GLM 5.2](https://allocate.network/models/z-ai-glm-5-2.md) · [GLM 5.3](https://allocate.network/models/z-ai-glm-5-3.md) · [Machine-readable catalog](https://allocate.network/catalog.json)