MiniMax vs Mistral: Token Pricing, Speed & Intelligence
Full comparison of MiniMax and Mistral — live token pricing, latency, throughput, context window, strengths, weaknesses, and best use cases. Updated July 2026.
MiniMax
Long-context frontier models with 1M token windows
MiniMax is a Chinese AI company offering the MiniMax M-series of large language models. MiniMax M2.7 and M1 support context windows up to 1M tokens and are designed for enterprise chat, long-document analysis, and agentic workflows.
Mistral
European frontier AI — Mistral Large, Codestral, and open models
Mistral AI is a Paris-based lab that trains both proprietary and open-weight models. Mistral Large competes with GPT-4 class models at lower prices, while Codestral is purpose-built for code generation with a 262K context window. Several Mistral models are open-weight and available for self-hosting.
Key metrics
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Live token pricing
Strengths & weaknesses
MiniMax
Mistral
Key differentiators
Frequently asked questions
MiniMax FAQs
What is MiniMax M2.7?
MiniMax M2.7 is MiniMax's latest chat model, supporting a 205K token context window. It is designed for enterprise chat, long-document analysis, and agentic tasks.
Is MiniMax available internationally?
Yes. The MiniMax API is accessible globally, and models are also available through OpenRouter and other inference aggregators.
Mistral FAQs
How much does the Mistral API cost?
Mistral Large costs $2.00/1M input and $6.00/1M output tokens. Mistral Small is $0.10/$0.30 per 1M tokens — one of the cheapest capable models available. Codestral for code generation is priced separately.
Are Mistral models open-weight?
Some are. Mistral 7B, Mixtral 8x7B, and Mixtral 8x22B are open-weight and available on Hugging Face for self-hosting. Mistral Large and Codestral are proprietary and only available via the API.
What is Codestral?
Codestral is Mistral's code-specialised model with a 262K context window. It supports 80+ programming languages and is optimised for code completion, generation, and explanation tasks.
Provider resources
MiniMax — Long-context frontier models with 1M token windows
MiniMax is a Chinese AI company offering the MiniMax M-series of large language models. MiniMax M2.7 and M1 support context windows up to 1M tokens and are designed for enterprise chat, long-document analysis, and agentic workflows.
MiniMax M1 supports a 1M token context window at $0.30/1M input tokens — one of the most cost-effective long-context models available.
Mistral — European frontier AI — Mistral Large, Codestral, and open models
Mistral AI is a Paris-based lab that trains both proprietary and open-weight models. Mistral Large competes with GPT-4 class models at lower prices, while Codestral is purpose-built for code generation with a 262K context window. Several Mistral models are open-weight and available for self-hosting.
The only frontier lab offering open-weight models alongside proprietary ones — giving teams the flexibility to self-host or use the API.
Key strengths compared
MiniMax
- ▸1M token context window
- ▸Competitive pricing
- ▸Strong multilingual performance
Mistral
- ▸Several open-weight models available for self-hosting
- ▸Codestral purpose-built for code with 262K context
- ▸European data sovereignty — GDPR-native
Provider category context
MiniMax is a frontier lab, founded in 2021. Mistral is a frontier lab, founded in 2023. Both are frontier lab providers — the comparison is primarily about pricing, model selection, and feature differentiation within the same tier.
How to choose between them
Both MiniMax and Mistral are frontier labs with proprietary models. Choose based on benchmark performance for your specific task: MiniMax leads on 1m token context window, while Mistral leads on several open-weight models available for self-hosting. For cost-sensitive workloads, compare the cheapest model tier from each provider in the pricing table above — the gap between efficient-tier models is often larger than between flagship models.