Model Cost Profile

Mistral: Mistral Small 3.1 24B

Developer: mistralai

Pricing updated Mar 11, 2026

Input rank: #182Output rank: #129

Live Pricing

Input: $0.3500

Output: $0.5600

Pricing via OpenRouter API ยท Last synced Mar 11, 2026

Mistral Small 3.1 24B, developed by mistralai, offers a substantial context window of 128,000 tokens, making it ideal for applications requiring extensive text analysis or long-form content generation. With an input price of $0.35 per million tokens and an output price of $0.56 per million tokens, teams can effectively manage their budget while leveraging this model for tasks such as customer support automation and complex data summarization. Its pricing structure allows for scalable deployment, accommodating both small projects and larger enterprise-level applications.

๐Ÿ‘ Vision

Context Window

128,000

Tokens

Input Price / 1M

$0.3500

Prompt tokens

Output Price / 1M

$0.5600

Completion tokens

Intelligence (MMLU)

Benchmark Pending

Massive Multitask Language Understanding

Price History

Mistral: Mistral Small 3.1 24B Pricing Trend

Input / 1M tokens0.0%Output / 1M tokens0.0%
Mar 7 โ€” Mar 11
$0.3500$0.4550$0.5600Mar 7Mar 8Mar 9Mar 10Mar 11

Current Input / 1M

$0.3500

Current Output / 1M

$0.5600

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FAQ

Common pricing and benchmark questions for Mistral: Mistral Small 3.1 24B.

How much does Mistral: Mistral Small 3.1 24B cost per 1M input tokens?

Mistral: Mistral Small 3.1 24B input pricing is $0.3500 per 1M tokens based on the latest synced provider data.

How much does Mistral: Mistral Small 3.1 24B cost per 1M output tokens?

Mistral: Mistral Small 3.1 24B output pricing is $0.5600 per 1M tokens based on the latest synced provider data.

What context window does Mistral: Mistral Small 3.1 24B support?

Mistral: Mistral Small 3.1 24B supports a context window of 128,000 tokens.

How can I compare Mistral: Mistral Small 3.1 24B with cheaper alternatives?

Use the comparison links on this page to open direct model-vs-model pricing and benchmark pages, then evaluate monthly spend projections for your workload.