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Mistral Small 4 (batch)

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Mistral's 24B small model: open-weights, fast, and strong on instruction following for its size.

Mistral Small 4 (batch) is a multimodal AI model from Mistral. It costs $0.075 per million input tokens and $0.300 per million output tokens (blended $0.142/M), with a 262,144-token context window.

Profile inherited from upstream Mistral Small 3.2 ↗ — this is a hosted variant of the same open-weights model.

INPUT
$0.075/M
per million input tokens
OUTPUT
$0.300/M
per million output tokens
BLENDED 70/30
$0.142/M
unchanged since 3 May
CONTEXT
262,144
tokens
What it is good at
  • Open weights (Apache 2.0)
  • Single-GPU friendly
  • 128K context
Typical use cases
  • Self-hosted production chat
  • Cheap European-hosted inference

Benchmarks

vs. best public score
Scores inherited from Mistral Small 3.2 — this is a hosted variant of the same open-weights model, so the underlying benchmark scores are identical.
MMLU71%
Multitask academic knowledge across 57 subjects.
Python function synthesis from docstrings.
LMArena Elo1175 Elo
Crowd-sourced head-to-head preference Elo rating.
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 Mistral Small 4 (batch) cost?

Mistral Small 4 (batch) costs $0.075 per million input tokens and $0.300 per million output tokens, for a blended reference rate of $0.142 per million tokens.

What is Mistral Small 4 (batch)'s context window?

Mistral Small 4 (batch) supports up to 262,144 tokens of context in a single request.

What is Mistral Small 4 (batch) best for?

Mistral Small 4 (batch) is well suited to Open weights (Apache 2.0), Single-GPU friendly and 128K context.

Who makes Mistral Small 4 (batch)?

Mistral Small 4 (batch) is developed and served by Mistral.

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