# GLM 5.2

> Frontier open-weight. #1 Intelligence Index among open models. 1M context, long-horizon agentic coding.

Human version: https://kymaapi.com/models/glm-5.2
Live JSON: `GET https://kymaapi.com/v1/models` (no auth required)

## Facts

- **Model ID**: `glm-5.2` — pass this as `model` in the request body
- **Creator**: Zhipu AI
- **Released**: 2026-06-16
- **Context window**: 1M tokens
- **Max output**: 131K tokens per response — a hard ceiling, not a default
- **Price**: $1.459 in / $4.984 out per 1M, cached input 10%
- **Capabilities**: tools, reasoning, caching
- **Alias**: `glm-flagship` resolves to this model

## Call it

```bash
curl https://kymaapi.com/v1/chat/completions \
  -H "Authorization: Bearer $KYMA_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"model": "glm-5.2", "messages": [{"role": "user", "content": "Hello"}]}'
```

## Positioning

Zhipu's newest frontier-open flagship on Kyma — the model the `glm-flagship` alias now resolves to — a 744B-parameter mixture-of-experts model with a 1M-token context window, built for long-horizon agentic coding.

## About

GLM 5.2 is the flagship of Zhipu's GLM line on Kyma and where the `glm-flagship` alias points. Released in June 2026 under the permissive MIT license, it is a mixture-of-experts model with roughly 744B total parameters and ~40B active per token, positioned squarely at coding and agentic workloads.

On the independent Intelligence Index v4.1 it scores 51 — the highest of any open-weight model, ahead of DeepSeek V4 Pro, MiniMax-M3, and Kimi K2.6, and ahead of several leading closed models. Through Kyma every call routes with automatic failover across multiple serving paths, so a degraded provider never surfaces as an error, and you reach it with the same OpenAI-compatible key as every other model.

The headline change over GLM 5.1 is context: the window grows from ~200K to a full 1M tokens, with output up to 131K. That holds an entire codebase plus an agent's working history in a single request. Function calling, structured outputs, and extended reasoning are all supported, and implicit prompt caching bills repeated prefixes at a steep discount — which matters for agents that resend a long system prompt on every step.

## Use cases

- **Long-horizon coding agents** — Its core design target — multi-step SWE tasks where the agent reads, edits, tests, and iterates across a repository over a long session.
- **Whole-repository context** — The 1M-token window lets an agent load a large codebase and its own history at once, instead of paging context in and out.
- **Complex reasoning** — Extended reasoning mode works through debugging, architecture decisions, and multi-constraint planning before committing to an answer.
- **Tool-calling pipelines** — Function calling plus structured outputs keep multi-step agent loops parseable and on schema, step after step.

## Not ideal for

Image inputs (it's text-only) or latency-sensitive chat UX — it's a medium-speed, premium-priced model that earns its cost on deep agentic work, not quick interactive replies.

## See also

- All models: https://kymaapi.com/models.md
- Pricing: https://kymaapi.com/pricing.md
- Other models by Zhipu AI: https://kymaapi.com/models?q=Zhipu%20AI