Mistral Large Instruct 2411
Mistral Large Instruct 2411 is a 123B parameter dense Large Language Model developed by Mistral, exceling in state-of-the-art reasoning, knowledge, and coding capabilities, with support for dozens of languages and over 80 coding languages. Its large context window of 131,072 tokens is a notable technical trait, enabling robust context adherence for various applications.
Input
Output
Context
131K
Max Output
16K
Parameters
122.6B
Technical Specifications
Input Modalities
Output Modalities
Capabilities
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Estimated GPU requirements for Mistral Large Instruct 2411
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 Large Instruct 2411
Answered from the entry's own fields: context, license, modalities, evidence, serving and the memory to self-host.
Mistral Large Instruct 2411 advertises a context window of 131,072 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 Large Instruct 2411 is an open-weight model released under the Other license, so the weights can be downloaded and self-hosted within that license's terms.
Mistral Large Instruct 2411 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.
No published benchmark result for Mistral Large Instruct 2411 is in the catalog yet, so the model is shown as unmeasured. It is not ranked or estimated; the router treats it as unknown for every task until a suite measures it.
Not on the managed pool today; Mistral Large Instruct 2411 is listed for reference and comparison. Connect your own provider key or endpoint that serves it and the gateway runs it on your account, with routing decisions recorded the same way.
About 119.0 GB at INT8 for the weights and a default context, from the catalog's 122.6B 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: Aug 28, 2026
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