Z.AI / zai/glm-5.3
GLM-5.3 - access through LLMTR
GLM-5.3 is Z.AI's flagship text model for long codebases, multi-step agent workflows, function calling, and terminal work with a 1M context window. Reasoning runs on every response and cannot be turned off; you tune its depth with the low, high, and max effort levels. LLMTR sends plain requests at low, and you can pick :high or :max for harder tasks. It does not accept image input.
Technical specifications
| Canonical ID | zai/glm-5.3 |
|---|---|
| Provider | Z.AI |
| Context window | 1,000,000 tokens |
| Operations | CHAT_COMPLETIONS |
| Modalities | text |
Pricing
An 8% platform margin applies to credit top-ups; model usage prices are not separately marked up.
| Operation | Metric | Unit | Price |
|---|---|---|---|
| CHAT_COMPLETIONS | INPUT_TEXT | PER_1M_TOKENS | $1.26 |
| CHAT_COMPLETIONS | CACHE_READ | PER_1M_TOKENS | $0.234000 |
| CHAT_COMPLETIONS | OUTPUT_TEXT | PER_1M_TOKENS | $3.96 |
Example usage
With existing OpenAI SDK flows, change only the base URL and model identifier.
curl https://llmtr.com/v1/chat/completions -H "Authorization: Bearer llmtr-your_key" -H "Content-Type: application/json" -d '{"model":"zai/glm-5.3","messages":[{"role":"user","content":"Hello"}]}'Guides about this model
- GLM-5.3: reasoning can't be turned off, choosing between low, high, and max - Many reasoning models let you turn thinking off entirely; GLM-5.3 doesn't offer that option. This article covers what that difference means and how to choose among its three effort levels.
- The reasoning-toggle difference between GLM-4.5-Air and GLM-5.3 - On GLM-5.3, reasoning is mandatory on every response. On GLM-4.5-Air, reasoning is a toggle — it can be turned on or off at will. This article covers what that difference means in practice.
- An EVREN alternative: the same OpenAI code, a two-line switch to LLMTR - Compares EVREN and LLMTR through the same OpenAI SDK code: the two lines that change, the LLMTR catalog counterparts of EVREN's models and their prices, context differences on the same models, and when each service makes sense.
- PentestCode LLMTR provider setup for authorised engagements - Working from the actual files on the PentestCode LLMTR branch, this guide covers key resolution, the seeded and live model catalog, and the request transform that normalises reasoning fields per model, all inside an authorised engagement scope.
- Pointing the OpenReview code review bot at LLMTR - OpenReview explores the repository on every review, so token spend follows the model you pick. In this branch swapping the gateway is not a code change but a matter of three environment variables.
Related models
- GLM-5.3-Flash zai/glm-5.3-flash
- GLM-5.3-FlashX zai/glm-5.3-flashx
- GLM-5.2 zai/glm-5.2
- GLM-5.1 zai/glm-5.1
- GLM-5 zai/glm-5
- GLM-5-Turbo zai/glm-5-turbo
- GLM-5V-Turbo zai/glm-5v-turbo
- GLM-4.7 zai/glm-4.7