GPT-4.1 mini vs Mistral Small

Mistral Small is cheaper for every workload modelled here.

List prices checked

Specifications and rates

PropertyGPT-4.1 miniMistral Small
Input per 1M$0.400$0.100
Output per 1M$1.60$0.300
Cached input per 1M$0.100
Blended (3:1)$0.700$0.150
Context window1M131K
Max output33K
Inputs acceptedtext, imagetext, image

Source: OpenAI pricing (May 2026) · Mistral AI 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.

WorkloadGPT-4.1 miniMistral SmallCheaper
In-app chat assistantA support or help assistant handling a few thousand conversations a month, with short prompts and short answers.$16$3.50Mistral Smallsaves $13/mo (78%)
RAG over documentsRetrieval-augmented answering where each request stuffs several retrieved passages into the prompt, so input dominates.$144$35Mistral Smallsaves $110/mo (76%)
Coding agentAn agentic loop that reads files and writes patches, generating heavy output and re-sending large context on every turn.$320$70Mistral Smallsaves $250/mo (78%)

What each one is for

GPT-4.1 mini

by OpenAI

The million-token context window at a fifth of the price, which is an unusual combination and the main reason this model is still in production stacks.

Mistral Small

by Mistral AI

An open-weight model available both as a hosted API and as a download, which makes it the cheap tier you can also run yourself if the economics change.

Common questions

Is GPT-4.1 mini or Mistral Small cheaper in 2026?
Mistral Small, for every workload modelled here. On a blended 3:1 basis it costs $0.150 per million tokens against GPT-4.1 mini's $0.700.
Which has the larger context window?
GPT-4.1 mini, at 1M 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 Small, at $0.300 per million output tokens against $1.60. 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 GPT-4.1 mini to Mistral Small worth it?
On price alone it is about 79% 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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