Mistral AI
Mistral-Large-Instruct-2411 is an advanced dense Large Language Model (LLM) of 123B parameters with state-of-the-art reasoning, knowledge and coding capabilities extending Mistral-Large-Instruct-2407 with better Long Context, Function Calling and System Prompt.
Mistral-Large-Instruct-2411 is an advanced dense Large Language Model (LLM) of 123B parameters with state-of-the-art reasoning, knowledge and coding capabilities extending Mistral-Large-Instruct-2407 with better Long Context, Function Calling and System Prompt.
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30.7
Quality Score
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Arena ELO
123B
Parameters
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Context
This measures the amount of verifiable public evidence we have, not how capable the model is. A missing field means it has not been verified yet, not that its value is zero.
15 of 22 public signals
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7.1K
Downloads
266
Likes
Nov 2024
Released
4/5 signals
3/4 signals
2/5 signals
3/4 signals
3/4 signals
Parameters
123B
Training compute
Not reported
Dataset scale
Not reported
Base model
Not reported
Gaps we are still tracking
Metadata sources
Launches
2
Benchmarks
12
General
8
Recent launch, pricing, benchmark, and API signals linked to this model or its provider.
Avg: 46.5 | IFEval: 84.0 | BBH: 52.7 | MATH: 49.5 | GPQA: 24.9 | MMLU-PRO: 50.7
Avg: 46.5 | IFEval: 84.0 | BBH: 52.7 | MATH: 49.5 | GPQA: 24.9 | MMLU-PRO: 50.7
View sourceAvg: 46.5 | IFEval: 84.0 | BBH: 52.7 | MATH: 49.5 | GPQA: 24.9 | MMLU-PRO: 50.7
View sourceAvg: 46.5 | IFEval: 84.0 | BBH: 52.7 | MATH: 49.5 | GPQA: 24.9 | MMLU-PRO: 50.7
View sourceMistral is bringing @aiDotEngineer back to Paris. After last year’s sold-out edition, our VP of Engineering Lélio Renard-Lavaud joins speakers from @bfl_ai , @cognition, @huggingface, and more. Explore the event and secure your spot: https://t.co/SyEfmXAdCF
Avg: 46.5 | IFEval: 84.0 | BBH: 52.7 | MATH: 49.5 | GPQA: 24.9 | MMLU-PRO: 50.7
Avg: 46.5 | IFEval: 84.0 | BBH: 52.7 | MATH: 49.5 | GPQA: 24.9 | MMLU-PRO: 50.7
Avg: 46.5 | IFEval: 84.0 | BBH: 52.7 | MATH: 49.5 | GPQA: 24.9 | MMLU-PRO: 50.7
Avg: 46.5 | IFEval: 84.0 | BBH: 52.7 | MATH: 49.5 | GPQA: 24.9 | MMLU-PRO: 50.7
Avg: 46.5 | IFEval: 84.0 | BBH: 52.7 | MATH: 49.5 | GPQA: 24.9 | MMLU-PRO: 50.7
Avg: 46.5 | IFEval: 84.0 | BBH: 52.7 | MATH: 49.5 | GPQA: 24.9 | MMLU-PRO: 50.7
Avg: 46.5 | IFEval: 84.0 | BBH: 52.7 | MATH: 49.5 | GPQA: 24.9 | MMLU-PRO: 50.7
Avg: 46.5 | IFEval: 84.0 | BBH: 52.7 | MATH: 49.5 | GPQA: 24.9 | MMLU-PRO: 50.7
Avg: 46.5 | IFEval: 84.0 | BBH: 52.7 | MATH: 49.5 | GPQA: 24.9 | MMLU-PRO: 50.7
Avg: 46.5 | IFEval: 84.0 | BBH: 52.7 | MATH: 49.5 | GPQA: 24.9 | MMLU-PRO: 50.7
Avg: 46.5 | IFEval: 84.0 | BBH: 52.7 | MATH: 49.5 | GPQA: 24.9 | MMLU-PRO: 50.7