Model Cost Profile

Mistral: Mixtral 8x22B Instruct

Developer: mistralai

Pricing updated Mar 11, 2026

Input rank: #280Output rank: #264

Live Pricing

Input: $2.00

Output: $6.00

Pricing via OpenRouter API ยท Last synced Mar 11, 2026

Mistral: Mixtral 8x22B Instruct, developed by mistralai, offers a substantial context window of 65,536 tokens, making it suitable for complex tasks such as long-form content generation and detailed data analysis. Teams utilizing this API model can expect an input cost of $2.00 per million tokens and an output cost of $6.00 per million tokens, which can influence budgeting for projects requiring extensive interactions. This model is particularly advantageous for applications in natural language understanding and instruction-following scenarios, where maintaining context over large text spans is critical.

๐Ÿ”ง Tool Calling๐Ÿ“‹ Structured Output

Context Window

65,536

Tokens

Input Price / 1M

$2.00

Prompt tokens

Output Price / 1M

$6.00

Completion tokens

Intelligence (MMLU)

Benchmark Pending

Massive Multitask Language Understanding

Price History

Mistral: Mixtral 8x22B Instruct Pricing Trend

Input / 1M tokens0.0%Output / 1M tokens0.0%
Mar 7 โ€” Mar 11
$2.00$4.00$6.00Mar 7Mar 8Mar 9Mar 10Mar 11

Current Input / 1M

$2.00

Current Output / 1M

$6.00

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FAQ

Common pricing and benchmark questions for Mistral: Mixtral 8x22B Instruct.

How much does Mistral: Mixtral 8x22B Instruct cost per 1M input tokens?

Mistral: Mixtral 8x22B Instruct input pricing is $2.00 per 1M tokens based on the latest synced provider data.

How much does Mistral: Mixtral 8x22B Instruct cost per 1M output tokens?

Mistral: Mixtral 8x22B Instruct output pricing is $6.00 per 1M tokens based on the latest synced provider data.

What context window does Mistral: Mixtral 8x22B Instruct support?

Mistral: Mixtral 8x22B Instruct supports a context window of 65,536 tokens.

How can I compare Mistral: Mixtral 8x22B Instruct 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.