Mistral AIMistral AI·💬 Text Generation

Mistral Small 3.2 24B Instruct

Function CallingWeb Searchfp8private
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Quick reference
Mistral Small 3.2 24B Instruct — TLDR
  • - 🏢 Built by Mistral AI, a Paris-based open-weight LLM company.
  • - 🆕 Incremental update to Mistral Small 3.1, same 24B architecture.
  • - 🎯 Tuned for better instruction following and fewer repetition errors.
  • - 🔧 Improved function/tool calling and structured-output reliability.
  • - 👁️ Multimodal: handles both image and text inputs.
  • - 📏 Long-context support, with this deployment exposing a large window.
  • - 🔒 Released under the permissive Apache 2.0 license.
  • - ⚡ Optimized for efficiency, balancing speed and capability.
💰 Pricing
$0.094 / $0.250
per 1M · input / output
📏 Context
256K tokens
📅 On Venice since
Jan 15, 2026
140 days ago
Provider

Mistral AI is a French artificial intelligence company headquartered in Paris, founded in 2023. The company focuses on developing large language models offered under both open-weight and proprietary licenses. Mistral AI has quickly risen to prominence in the…

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2 models on Venice
2 text
Since Jan 15, 2026

About this model

Mistral Small 3.2 24B Instruct is a 24-billion-parameter model from Mistral AI, a French lab known for open-weight releases under permissive licenses. According to Mistral's own documentation, it is an update of Mistral-Small-3.1-24B-Instruct, keeping the same 24B architecture while refining behavior rather than scaling up. It is distributed under Apache 2.0 and supports both image and text inputs, function calling, and structured outputs.

Compared with its 3.1 predecessor, Mistral's documentation describes version 3.2 as focusing on enhanced instruction following, reduced repetition and "infinite generation" errors, and more robust function calling and structured output. The lab frames this as a targeted refinement of the existing model rather than a broad capability leap, with most other categories expected to match or slightly improve on Small 3.1.

On this Venice deployment, the model runs in fp8 quantization with a large context window and adds web-search capability, alongside its native function calling.

Within the same family, the newer Mistral Small 4 is a larger, later release, marking a different design point from this efficiency-oriented 24B model. For users wanting a compact, openly licensed model that balances speed with multimodal and tool-use capability, Mistral Small 3.2 remains a practical general-purpose option.

This About section is AI-generated from public sources (Claude Opus 4.8), with no human editing. It may contain inaccuracies — verify critical details against the sources listed above.

Data sources: Venice API · HuggingFace · Wikipedia — enrichment updated 1d ago