Zai Glm 5.3 Flash
At a glance
- Price per 1M tokens (input)
- $0.15
- Price per 1M tokens (output)
- $0.50
- Context
- 1,048,576 tokens
- Free access
- yes (see below)
Refreshed daily; data verified October 26, 2026. Published October 26, 2026.
Zai Glm 5.3 Flash by Mistral AI is a multimodal language model built for developers and business teams that need to process text and images together. It suits document analysis, visual question answering, and workflows that connect to external services through tool calling, which lets the model invoke functions or APIs to perform actions. Mistral's approach emphasizes efficient inference and open-weight release strategies so organizations can deploy capable models without excessive infrastructure overhead. The model also supports step-by-step reasoning to improve accuracy on multi-stage tasks.
Specifications & pricing
| Input (per 1M tokens) | $0.15 |
|---|---|
| Output (per 1M tokens) | $0.50 |
| Cache read (per 1M tokens) | $0.03 |
| Context window | 1,048,576 tokens |
| Max output | 131,072 tokens |
| Capabilities | images, tool calling, reasoning |
LiteLLM community dataset (MIT), verified October 26, 2026. Official Mistral AI pricing.
What Zai Glm 5.3 Flash would cost on your workload — run it through the cost calculator →
Where to try Zai Glm 5.3 Flash for free
- Mistral AI offers a free chat — Le Chat (free plan). A vendor's free chat may run a different model from the same family — the exact model is not guaranteed.
Frequently asked questions
What is this model good for?+
It handles image understanding, tool calling, and step-by-step reasoning. Common uses include extracting information from scanned documents, answering questions about charts or photos, and building agents that can call external functions to retrieve data or complete transactions.
How do I get started?+
Access the model through Mistral's platform or supported cloud providers. You will need an API key, then you can send prompts that include text, images, or both, and define functions for the model to call when needed.
How does it differ from other models in the line?+
This variant is optimized for speed and lower resource use while keeping multimodal and tool-use abilities. Other models in the family may prioritize maximum reasoning depth or larger context windows at the cost of higher latency.
What are the limitations?+
It can still misinterpret complex images or produce incorrect function arguments. Step-by-step reasoning improves reliability but does not eliminate errors, so critical outputs should be reviewed by a person.
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