DeepScaleRAgentica Project
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Smaug-72BAbacus
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About
DeepScaleR is a 1.5-billion-parameter language model fine-tuned from DeepSeek-R1-Distilled-Qwen-1.5B using distributed reinforcement learning and a novel iterative context-lengthening strategy that gradually increases its context window from 8K to 24K tokens during training. It was trained on ~40,000 carefully curated mathematical problems drawn from competition-level datasets like AIME (1984–2023), AMC (pre-2023), Omni-MATH, and STILL. DeepScaleR achieves 43.1% accuracy on AIME 2024, a roughly 14.3 percentage point boost over the base model, and surpasses the performance of the proprietary O1-Preview model despite its much smaller size. It also posts strong results on a suite of math benchmarks (e.g., MATH-500, AMC 2023, Minerva Math, OlympiadBench), demonstrating that small, efficient models tuned with RL can match or exceed larger baselines on reasoning tasks.
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About
Smaug-72B is a powerful open-source large language model (LLM) known for several key features:
High Performance: It currently holds the top spot on the Hugging Face Open LLM leaderboard, surpassing models like GPT-3.5 in various benchmarks. This means it excels at tasks like understanding, responding to, and generating human-like text.
Open Source: Unlike many other advanced LLMs, Smaug-72B is freely available for anyone to use and modify, fostering collaboration and innovation in the AI community.
Focus on Reasoning and Math: It specifically shines in handling reasoning and mathematical tasks, attributing this strength to unique fine-tuning techniques developed by Abacus AI, the creators of Smaug-72B.
Based on Qwen-72B: It's technically a fine-tuned version of another powerful LLM called Qwen-72B, released by Alibaba, further improving upon its capabilities.
Overall, Smaug-72B represents a significant step forward in open-source AI.
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Platforms Supported
Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook
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Platforms Supported
Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook
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Audience
Researchers, students, and developers interested in an AI model capable of mathematical reasoning and logic tasks without requiring heavy hardware
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Audience
AI developers interested in a powerful large language model
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Support
Phone Support
24/7 Live Support
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Support
Phone Support
24/7 Live Support
Online
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API
Offers API
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API
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Screenshots and Videos |
Screenshots and VideosNo images available
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Pricing
Free
Free Version
Free Trial
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Pricing
Free
Free Version
Free Trial
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Reviews/
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Training
Documentation
Webinars
Live Online
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Training
Documentation
Webinars
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Company InformationAgentica Project
Founded: 2025
United States
agentica-project.com
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Company InformationAbacus
Founded: 2019
United States
huggingface.co/abacusai/Smaug-72B-v0.1
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