# GLM 5.1 FP4 vs GLM 5.3

On provider list prices, GLM 5.1 FP4 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 5.1 FP4 | GLM 5.3 |
| --- | --- | --- |
| Lab | Z.ai | Z.ai |
| Access | Open weights | Open weights |
| Context window | 198K 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 5.1 FP4 and $3,220 on GLM 5.3 at list: a gap of $0.

GLM 5.3 reads 1M tokens per request against 198K for GLM 5.1 FP4, 5.2x the window. That decides which one can take whole documents without splitting them.

## Choose GLM 5.1 FP4 for

- Training toward a model you own

## Choose GLM 5.3 for

- The longer context window (1M vs 198K tokens)

## Common questions

### Which is cheaper, GLM 5.1 FP4 or GLM 5.3?

GLM 5.1 FP4, 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?

GLM 5.3: 1,048,575 tokens (1M) against 202,752 (198K) for GLM 5.1 FP4.

### Can I fine-tune GLM 5.1 FP4 or GLM 5.3?

Both publish open weights (GLM 5.1 FP4: 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-5-1-vs-z-ai-glm-5-3) · [GLM 5.1 FP4](https://allocate.network/models/z-ai-glm-5-1.md) · [GLM 5.3](https://allocate.network/models/z-ai-glm-5-3.md) · [Machine-readable catalog](https://allocate.network/catalog.json)