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Mistral-Small-24B-Base-2501-ungated
adamo1139/Mistral-Small-24B-Base-2501-ungated
Mistral-Small-24B-Base-2501-ungated is a machine learning model from adamo1139. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for vllm. The card lists the license as apache-2.0.
Mistral Small 3 ( 2501 ) sets a new benchmark in the "small" Large Language Models category below 70B, boasting 24B parameters and achieving state-of-the-art capabilities comparable to larger models! Check out our fin…
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At a glance
- Library
- vllm
- License
- apache-2.0
- Model type
- mistral
- Access
- Public
- Created
- Jan 30, 2025
- Updated
- Jan 30, 2025
- SHA
- eb356d1f
Model card
From the Hugging Face model README
Model Card for Mistral-Small-24B-Base-2501
Mistral Small 3 ( 2501 ) sets a new benchmark in the "small" Large Language Models category below 70B, boasting 24B parameters and achieving state-of-the-art capabilities comparable to larger models!
Check out our fine-tuned Instruct version Mistral-Small-24B-Instruct-2501.
For enterprises that need specialized capabilities (increased context, particular modalities, domain specific knowledge, etc.), we will be releasing commercial models beyond what Mistral AI contributes to the community.
This release demonstrates our commitment to open source, serving as a strong base model.
Learn more about Mistral Small in our blog post.
Key Features
- Multilingual: Supports dozens of languages, including English, French, German, Spanish, Italian, Chinese, Japanese, Korean, Portuguese, Dutch, and Polish.
- Advanced Reasoning: State-of-the-art conversational and reasoning capabilities.
- Apache 2.0 License: Open license allowing usage and modification for both commercial and non-commercial purposes.
- Context Window: A 32k context window.
- Tokenizer: Utilizes a Tekken tokenizer with a 131k vocabulary size.
Benchmark Results
| Benchmark | Metric | Mistral-Small-24B-Base |
|---|---|---|
| MMLU | 5-shot | 80.73 |
| MMLU Pro | 5-shot, CoT | 54.37 |
| GPQA Main | 5-shot, CoT | 34.37 |
| TriviaQA | 5-shot | 80.32 |
| ARC-c | 0-shot | 91.29 |
| TriviaQA | 5-shot | 76.6 |
| MBPP | pass@1 | 69.64 |
| GSM8K | 5-shot, maj@1 | 80.73 |
| MATH | 4-shot, MaJ | 45.98 |
| AGIEval | - | 65.80 |
| Benchmark | Metric | Mistral-Small-24B-Base |
|---|---|---|
| French MMLU | - | 78.03 |
| German MMLU | - | 77.69 |
| Spanish MMLU | - | 78.86 |
| Russian MMLU | - | 75.64 |
| Chinese MMLU | - | 70.35 |
| Korean MMLU | - | 56.42 |
| Japanese MMLU | - | 74.46 |
The Mistral AI Team
Albert Jiang, Alexandre Sablayrolles, Alexis Tacnet, Alok Kothari, Antoine Roux, Arthur Mensch, Audrey Herblin-Stoop, Augustin Garreau, Austin Birky, Bam4d, Baptiste Bout, Baudouin de Monicault, Blanche Savary, Carole Rambaud, Caroline Feldman, Devendra Singh Chaplot, Diego de las Casas, Diogo Costa, Eleonore Arcelin, Emma Bou Hanna, Etienne Metzger, Gaspard Blanchet, Gianna Lengyel, Guillaume Bour, Guillaume Lample, Harizo Rajaona, Henri Roussez, Hichem Sattouf, Ian Mack, Jean-Malo Delignon, Jessica Chudnovsky, Justus Murke, Kartik Khandelwal, Lawrence Stewart, Louis Martin, Louis Ternon, Lucile Saulnier, Lélio Renard Lavaud, Margaret Jennings, Marie Pellat, Marie Torelli, Marie-Anne Lachaux, Marjorie Janiewicz, Mickaël Seznec, Nicolas Schuhl, Niklas Muhs, Olivier de Garrigues, Patrick von Platen, Paul Jacob, Pauline Buche, Pavan Kumar Reddy, Perry Savas, Pierre Stock, Romain Sauvestre, Sagar Vaze, Sandeep Subramanian, Saurabh Garg, Sophia Yang, Szymon Antoniak, Teven Le Scao, Thibault Schueller, Thibaut Lavril, Thomas Wang, Théophile Gervet, Timothée Lacroix, Valera Nemychnikova, Wendy Shang, William El Sayed, William Marshall
- Library
- vllm
- Type
- mistral
- License
- apache-2.0
- Languages
- en, fr, de, es, it, pt
- Created
- Jan 30, 2025
- Updated
- Jan 30, 2025