Mistral Small 24B Instruct 2501
Mistral Small 24B Instruct 2501 is a chat model developed by Mistral, boasting 24B parameters and a 32,768 token context window, making it suitable for fast response conversational agents and low latency function calling. It is genuinely best at providing agentic capabilities with native function calling and JSON outputting, as well as advanced reasoning and conversational capabilities.
Input
Output
Context
33K
Max Output
16K
Parameters
23.6B
Technical Specifications
Input Modalities
Output Modalities
Capabilities
Loading capabilities…
Benchmarks
Estimated GPU requirements for Mistral Small 24B Instruct 2501
Estimates based on INT8 quantization at up to 32K context. A count above one assumes tensor parallelism across the cards. Actual requirements vary by framework and configuration.
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Frequently asked questions about Mistral Small 24B Instruct 2501
Answered from the entry's own fields: context, license, modalities, evidence, serving and the memory to self-host.
Mistral Small 24B Instruct 2501 advertises a context window of 32,768 tokens, with a maximum output of 16,384 tokens in a single response. The figure is the creator's published maximum; a given host may serve less, and the gateway routes on what each host actually serves.
Yes. Mistral Small 24B Instruct 2501 is an open-weight model released under the Apache 2.0 license, so the weights can be downloaded and self-hosted within that license's terms.
Mistral Small 24B Instruct 2501 accepts Text and produces Text. The capabilities card on this page lists which API features each deployment honours, such as function calling and structured output, with the source each was checked against.
Mistral Small 24B Instruct 2501 has published results from Artificial Analysis, shown by suite in the benchmarks card above exactly as the publisher reported them. Scores are not combined across suites, and a suite that has not measured Mistral Small 24B Instruct 2501 is shown as not available rather than estimated.
Yes. Mistral Small 24B Instruct 2501 is served on the managed pool through the OpenAI-compatible endpoint as mistralai/Mistral-Small-24B-Instruct-2501, pinned by name or chosen by routing when it is the best fit for a request. The Try in Playground button opens it directly.
About 23.3 GB at INT8 for the weights and a default context, from the catalog's 23.6B parameter count; FP16 needs roughly twice that, and long contexts or many concurrent requests add KV cache on top. The GPU section on this page lists cards that hold it, and the capacity planner sizes it for your context length and traffic.
Fields collected from public registries, host APIs and benchmark publishers, each tagged with its source.
Last updated: Sep 13, 2026
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