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Codestral 2508 (batch)

Name: Codestral 2508 (batch)
Brand: Mistral
Price: 0.300000 USD

text+file->text

Code-specialist model from Mistral. 256K context fits whole repos and 80+ programming languages.

Codestral 2508 (batch) is a efficient AI model from Mistral. It costs $0.300 per million input tokens and $0.900 per million output tokens (blended $0.480/M), with a 256,000-token context window.

Profile inherited from upstream Codestral ↗ — this is a hosted variant of the same open-weights model.

Modalities textOfficial model page ↗Provider pricing ↗API docs ↗Pricing source ↗Compare with another model →Estimate monthly cost →

INPUT

$0.300/M

per million input tokens

OUTPUT

$0.900/M

per million output tokens

BLENDED 70/30

$0.480/M

unchanged since 3 May

default reference rate · how it is calculated →

CONTEXT

256,000

tokens

What it is good at

Code-tuned
256K context
80+ languages

Typical use cases

IDE autocomplete
Code review
Repo Q&A

Benchmarks

vs. best public score

Scores inherited from Codestral — this is a hosted variant of the same open-weights model, so the underlying benchmark scores are identical.

MATH51%

High-school competition math problems.

HumanEval85%

Python function synthesis from docstrings.

Hand-curated from each provider's published reports and public leaderboards. Methodology varies across sources, treat as directional rather than authoritative.

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Frequently asked questions

How much does Codestral 2508 (batch) cost?

Codestral 2508 (batch) costs $0.300 per million input tokens and $0.900 per million output tokens, for a blended reference rate of $0.480 per million tokens.

What is Codestral 2508 (batch)'s context window?

Codestral 2508 (batch) supports up to 256,000 tokens of context in a single request.

What is Codestral 2508 (batch) best for?

Codestral 2508 (batch) is well suited to Code-tuned, 256K context and 80+ languages.

Who makes Codestral 2508 (batch)?

Codestral 2508 (batch) is developed and served by Mistral.

Terms used on this page

Full glossary →

Token Input tokens Output tokens Price per million tokens Context window Prompt caching Batch API Blended cost