# Coding GLM 5.3

Model id on AIHubMix: `coding-glm-5.3`
Create an API key: https://console.aihubmix.com/?utm_source=llms-agent&utm_medium=model-llms

> GLM-5.3 is Z.ai’s reasoning model for coding and agentic workflows, designed for complex software engineering, long-running agents, and vulnerability analysis. It uses the same base model as GLM-5.2, with scaled post-training improving coding, task execution, and token efficiency.

This model is a limited-time preview version of GLM-5.3, intended for testing and evaluation only. Service stability is not guaranteed, and we do not recommend using it in production environments. We’re waiting for the official commercial API release and will integrate it as soon as official support becomes available.

- Developer: Z.AI
- Input modalities: text
- Capabilities: Thinking, Streaming, Tool calling, Structured outputs, Prompt caching
- Release date: 2026-08-14
- Pricing: $0.06/M input tokens, $0.22/M output tokens, $0.015/M cached input

## Endpoints (base URL: https://aihubmix.com)

- `POST /v1/chat/completions` — OpenAI Chat Completions (`Authorization: Bearer $AIHUBMIX_API_KEY`)
- `POST /v1/messages` — Anthropic Messages (`x-api-key: $AIHUBMIX_API_KEY` + `anthropic-version: 2023-06-01`)

## Example

```bash
curl -s https://aihubmix.com/v1/chat/completions \
  -H "Authorization: Bearer $AIHUBMIX_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"model":"coding-glm-5.3","messages":[{"role":"user","content":"Hello"}]}'
```

## Response

Without `stream`, `/v1/chat/completions` returns a standard Chat Completions object:

```json
{"id":"...","object":"chat.completion","model":"coding-glm-5.3","choices":[{"message":{"role":"assistant","content":"..."}}],"usage":{"prompt_tokens":12,"completion_tokens":24,"total_tokens":36}}
```

With `"stream": true` the response is `text/event-stream`: read each `data:` JSON chunk until `data: [DONE]`. The Messages and Gemini endpoints return their protocols' native response shapes (Anthropic / Google).

## Errors

Error responses carry a `tid` (trace id) — include it when contacting support. Reference: https://docs.aihubmix.com/en/FAQs/HTTP-Codes.md

- 400 — parameter error; most are passed through from the upstream provider (media: `prompt_missing`, `size_not_supported`, `n_not_within_range`, …)
- 401 — missing `Authorization` header, or the key is invalid/expired
- 403 — `insufficient_user_quota` (top up at https://console.aihubmix.com/?utm_source=llms-agent&utm_medium=model-llms), account suspended, or this key is not allowed to use this model
- 429 — rate limited; back off and retry
- 503 — no channel can serve the request (check the model id and your access), or the upstream provider is throttling; retry later

## More

- Model page: https://aihubmix.com/model/coding-glm-5.3
- Try in browser: https://playground.aihubmix.com/?model=coding-glm-5.3
- Compare with another model (human-facing, side-by-side specs and pricing): https://aihubmix.com/compare — pick this model and a peer there; published pairs are listed in https://aihubmix.com/sitemap-compare.xml, unpublished pairs 404 so do not compose the path by hand
- Full parameter schema (machine-readable, authoritative): https://aihubmix.com/model-data/models/coding-glm-5.3.5df68331.json — per-protocol parameters with types, ranges, enums and defaults. Refreshed together with this page; if it ever 404s, re-resolve via `https://aihubmix.com/model-data/index.json` (find this id, fetch its `path`)
- Generate runnable code programmatically: npm `@aihubmix/codegen` — the generator behind the Playground's "Get Code" (4 protocols × 7 languages, media endpoints included); the body it builds is the exact wire body the Playground sends, so generated snippets and real requests cannot diverge. `@aihubmix/model-schema` (npm) translates the parameter schema above into codegen input
- Site index for agents: https://aihubmix.com/llms.txt · Onboarding: https://aihubmix.com/agents.md

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Canonical version of this document: https://aihubmix.com/model/coding-glm-5.3/llms.txt