Mistral Large 4
At a glance
- Price per 1M tokens (input)
- $0.68
- Price per 1M tokens (output)
- $2.09
- Context
- 524,288 tokens
- Free access
- yes (see below)
Refreshed daily; data verified October 8, 2026. Published October 8, 2026.
Mistral Large 4 by Mistral AI is designed for enterprise users who need a model capable of understanding visual inputs, executing external functions through tool calling, and performing multi-step reasoning tasks. It suits workflows involving document analysis with embedded images, automated data retrieval via APIs, and complex decision-making processes that require chaining logical steps. Mistral AI’s approach emphasizes open-weight models with strong alignment to safety and controllability, allowing organizations to deploy the model in regulated environments while maintaining transparency over its behavior.
Specifications & pricing
| Input (per 1M tokens) | $0.68 |
|---|---|
| Output (per 1M tokens) | $2.09 |
| Cache read (per 1M tokens) | $0.068 |
| Context window | 524,288 tokens |
| Capabilities | images, tool calling, reasoning |
LiteLLM community dataset (MIT), verified October 8, 2026. Official Mistral AI pricing.
What Mistral Large 4 would cost on your workload — run it through the cost calculator →
Where to try Mistral Large 4 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 types of tasks benefit most from Mistral Large 4’s image understanding capability?+
Tasks such as interpreting charts in reports, extracting text from scanned forms, or analyzing product images for quality checks benefit from its ability to process visual content alongside textual prompts, enabling richer context in automated workflows.
How does tool calling work in this model, and why is it useful for business applications?+
Tool calling allows the model to invoke external functions like database queries or API calls when needed, enabling it to retrieve real-time data or perform actions beyond its training knowledge, which is useful for dynamic business processes such as inventory checks or customer service automation.
How does Mistral Large 4 differ from smaller models in the Mistral line, such as Mistral Small or Medium variants?+
Compared to smaller variants, Mistral Large 4 offers stronger performance in complex reasoning and multimodal understanding while maintaining efficient inference, making it suitable for high-stakes applications where accuracy and depth of analysis are prioritized over minimal latency.
What are the key limitations a business user should consider before deploying Mistral Large 4?+
The model may occasionally produce incorrect inferences when visual inputs are ambiguous or low quality, and its tool calling behavior depends on proper function definitions and environment setup, requiring careful integration testing to avoid unintended actions in production systems.
Compare with others
Org chart: how to move your company onto AI
A practical map: which company roles and processes AI agents can take over, where to start, and in what order to roll it out.