Mistral Large 4
Pricing & Specs
Mistral · $0.7 input / $2.1 output per 1M tokens · 1M context window
The per-token price never tells the full story. A typical task (1K input + 500 output tokens) on Mistral Large 4 costs about $0.0017, roughly $1.75 per 1,000 runs. But if it needs 3x the tokens of a cheaper model to match quality on YOUR task, the economics flip. The only way to know is to benchmark it on your actual workload.
Mistral Large 4 API Pricing
| Tokens | Price |
|---|---|
| Input | $0.7 / 1M tokens |
| Output | $2.1 / 1M tokens |
| Cached input | $0.07 / 1M tokens |
Cached input at 10% of input. Batch API at 50%.
What that means in practice
Mistral Large 4 Specs
| Spec | Value |
|---|---|
| Context window | 1M tokens |
| Input modalities | text, image |
| Output modalities | text |
| Reasoning model | No |
| Tool / function calling | Yes |
| JSON mode | Yes |
| Streaming | Yes |
| Prompt caching | Yes |
| Batch API | Yes |
Capabilities
Notes
Released October 6, 2026 (public preview). Open-weight general-purpose multimodal MoE: 52B active / 1.05T total parameters, 1.6B vision encoder. Supersedes Mistral Large 3 (mistral-large-2512).
FAQ
How much does Mistral Large 4 cost?
Mistral Large 4 costs $0.7 per 1M input tokens and $2.1 per 1M output tokens ($0.07 per 1M cached input tokens).
What is Mistral Large 4's context window?
Mistral Large 4 has a 1M-token context window.
Can I test Mistral Large 4 on my own task?
Yes. OpenMark lets you benchmark Mistral Large 4 against 100+ models on your own task with real API calls, with no API keys needed, free tier available.
Is Mistral Large 4 the right model for YOUR task?
Pricing tables can't answer that. Benchmark it against 100+ models
on your actual workload: real API calls, real costs. Free tier available.