# Kimi K2.5 vs GLM 5.2

On provider list prices, Kimi K2.5 costs $0.50 per million input tokens against $1.40 for GLM 5.2: 2.8x apart. Output is $2.80 against $4.40 (1.6x). On Allocate both bill at list plus the 7% transaction fee.

## Specifications

| | Kimi K2.5 | GLM 5.2 |
| --- | --- | --- |
| Lab | Togethercomputer | Zai Org |
| Access | Open weights | Open weights |
| Context window | 256K tokens | 256K tokens |
| List price, input | $0.50 / M tokens | $1.40 / M tokens |
| List price, output | $2.80 / M tokens | $4.40 / M tokens |
| Cached input | n/a | $0.26 / M tokens |
| License | Not listed | Not listed |
| Fine-tunable | Yes | Yes |

Specifications and provider list prices from the Allocate catalog, checked 2026-07-08. Billed price is list plus the 7% transaction fee.

## What the numbers say

Take 1,000,000 requests a month at 1,200 input and 350 output tokens each. That workload costs $1,580 a month on Kimi K2.5 and $3,220 on GLM 5.2 at list: a gap of $1,640, or 2.0x.

## Choose Kimi K2.5 for

- Whole-document reasoning
- Long-context retrieval
- Open-weight fine-tuning

## Choose GLM 5.2 for

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

## Common questions

### Which is cheaper, Kimi K2.5 or GLM 5.2?

Kimi K2.5, on this workload shape. At list prices it is $0.50/$2.80 per million tokens in and out against $1.40/$4.40 for GLM 5.2. Billed on Allocate: $0.54/$3.00 against $1.50/$4.71, list plus 7%.

### Which has the bigger context window?

They match: both read 262,144 tokens (256K) per request.

### Can I fine-tune Kimi K2.5 or GLM 5.2?

Both publish open weights (Kimi K2.5: Not listed; GLM 5.2: 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/kimi-k2-5-vs-z-ai-glm-5-2) · [Kimi K2.5](https://allocate.network/models/kimi-k2-5.md) · [GLM 5.2](https://allocate.network/models/z-ai-glm-5-2.md) · [Machine-readable catalog](https://allocate.network/catalog.json)