Mistral Medium 2508
Mistral AI
At a glance
- Price per 1M tokens (input)
- $0.40
- Price per 1M tokens (output)
- $2.00
- Context
- 131,072 tokens
- Free access
- yes (see below)
Refreshed daily; data verified August 15, 2026. Published August 12, 2026.
The Mistral Medium model is designed for businesses and organizations that require a robust image understanding and tool calling capability. Tool calling refers to the ability of the model to invoke external functions or tools to perform specific tasks, enhancing its overall functionality. This model is well-suited for tasks that involve analyzing and interpreting visual data, and then using that information to trigger actions or decisions. The vendor's approach distinguishes itself through its focus on providing a seamless integration between image understanding and tool calling, allowing users to leverage the strengths of both capabilities in a cohesive manner. By doing so, it enables users to automate complex workflows and decision-making processes more effectively.
Specifications & pricing
| Input (per 1M tokens) | $0.40 |
|---|---|
| Output (per 1M tokens) | $2.00 |
| Context window | 131,072 tokens |
| Max output | 131,072 tokens |
| Capabilities | images, tool calling |
LiteLLM community dataset (MIT), verified August 15, 2026. Official Mistral AI pricing.
What Mistral Medium 2508 would cost on your workload — run it through the cost calculator →
Where to try Mistral Medium 2508 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+
This model is particularly useful for applications that require the analysis of visual data and the subsequent triggering of specific actions or decisions based on that analysis, such as quality control inspections or automated decision-making systems
How do I get started with this model+
To get started, users should familiarize themselves with the model's capabilities and limitations, and then design a workflow that integrates the model's image understanding and tool calling capabilities to meet their specific needs
How does this model differ from other models in the line+
This model differs from its counterparts in its balanced approach to image understanding and tool calling, making it a versatile option for a wide range of applications that require both capabilities
What are the limitations of this model+
The model's limitations include its reliance on the quality of the input visual data and the compatibility of the external tools or functions it is designed to call, which can affect its overall performance and effectiveness
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