Mistral Large vs OpenAI o3

Mistral Large is cheaper for every workload modelled here.

List prices checked

Specifications and rates

PropertyMistral LargeOpenAI o3
Input per 1M$2.00$2.00
Output per 1M$6.00$8.00
Cached input per 1M$0.500
Blended (3:1)$3.00$3.50
Context window131K200K
Max output100K
Inputs acceptedtexttext, image

Source: Mistral AI pricing (May 2026) · OpenAI pricing (May 2026). Published list prices only — committed-use discounts, regional variation, and per-request charges are not included. Not yet independently re-checked against the vendor’s page.

Monthly cost by workload

Identical token volumes through both rate cards. Output-heavy profiles are where the ranking flips.

WorkloadMistral LargeOpenAI o3Cheaper
In-app chat assistantA support or help assistant handling a few thousand conversations a month, with short prompts and short answers.$70$80Mistral Largesaves $10/mo (13%)
RAG over documentsRetrieval-augmented answering where each request stuffs several retrieved passages into the prompt, so input dominates.$690$720Mistral Largesaves $30/mo (4%)
Coding agentAn agentic loop that reads files and writes patches, generating heavy output and re-sending large context on every turn.$1,400$1,600Mistral Largesaves $200/mo (13%)

What each one is for

Mistral Large

by Mistral AI

The French lab's flagship, priced below every US frontier model and hosted in the EU, which is often the deciding factor rather than the benchmark scores.

OpenAI o3

by OpenAI

A reasoning model that spends tokens thinking before answering. The list price understates the real cost, because reasoning tokens bill as output and can dominate the total.

Common questions

Is Mistral Large or OpenAI o3 cheaper in 2026?
Mistral Large, for every workload modelled here. On a blended 3:1 basis it costs $3.00 per million tokens against OpenAI o3's $3.50.
Which has the larger context window?
OpenAI o3, at 200K tokens against 131K. A larger window only helps if you can afford to fill it — the cost of one full-context request is in the table above.
Which is cheaper for output-heavy work like agents?
Mistral Large, at $6.00 per million output tokens against $8.00. Reasoning tokens bill as output, so for agentic loops this axis usually decides the invoice regardless of what the input rates look like.
What is not included in these figures?
Batch-processing discounts, fine-tuning, long-context surcharges above a provider's standard tier, and any enterprise agreement. These are published pay-as-you-go list prices, checked against each provider's own pricing page on the date shown.
Is switching from OpenAI o3 to Mistral Large worth it?
On price alone it is about 14% cheaper on a blended basis. Whether that survives contact with your workload depends on output quality and on retry rate — a cheaper model that needs two attempts is not cheaper. Model the specific volumes in the calculator before you migrate.

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