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A group of researchers has launched Gentle-R1-32B, a brand new open-source AI mannequin optimized for fixing superior math issues, making it out there on Hugging Face beneath a permissive Apache 2.0 license — free for enterprises and researchers to take, deploy, fine-tune or modify as they need, even for business functions.
The 32-billion parameter (variety of mannequin settings) mannequin surpasses the efficiency of equally sized (and even bigger) open supply fashions comparable to DeepSeek-R1-Distill-Llama-70B and DeepSeek-R1-Distill-Qwen-32B on third-party benchmark the American Invitational Arithmetic Examination (AIME), which incorporates 15 math issues designed for very superior college students and has an allotted time restrict of three hours for human customers.

Developed by Liang Wen, Fenrui Xiao, Xin He, Yunke Cai, Qi An, Zhenyu Duan, Yimin Du, Junchen Liu, Lifu Tang, Xiaowei Lv, Haosheng Zou, Yongchao Deng, Shousheng Jia, and Xiangzheng Zhang, the mannequin surpasses earlier open-source options on aggressive math benchmarks.
Extremely, the researchers accomplished the mannequin’s coaching in fewer than six hours on 12 Nvidia H800 GPUs at an estimated whole price of $1,000. This makes Gentle-R1-32B some of the accessible and sensible approaches for growing high-performing math-specialized AI fashions. Nevertheless, it’s essential to recollect the mannequin was educated on a variant of Alibaba’s open supply Qwen 2.5-32B-Instruct, which itself is presumed to have had a lot larger upfront coaching prices.
Alongside the mannequin, the group has launched its coaching datasets, coaching scripts, and analysis instruments, offering a clear and accessible framework for constructing math-focused AI fashions.
The arrival of Gentle-R1-32B follows different comparable efforts from rivals comparable to Microsoft with its Orca-Math collection.
A brand new math king emerges
Gentle-R1-32B is designed to deal with complicated mathematical reasoning, significantly on the AIME (American Invitational Arithmetic Examination) benchmarks.
It was educated from Qwen2.5-32B-Instruct, ranging from a mannequin with out long-chain-of-thought (COT) reasoning. The group utilized curriculum-based supervised fine-tuning (SFT) and Direct Desire Optimization (DPO) to refine its problem-solving capabilities.
When evaluated, Gentle-R1-32B achieved 76.6 on AIME24 and 64.6 on AIME25, surpassing DeepSeek-R1-Distill-Qwen-32B, which scored 72.6 and 54.9, respectively.
This enchancment means that the curriculum-based coaching strategy successfully enhances mathematical reasoning, even when coaching from fashions that originally lack lengthy COT.
Truthful benchmarking
To make sure honest benchmarking, the group decontaminated coaching knowledge towards widespread reasoning benchmarks, together with AIME24/25, MATH-500, and GPQA Diamond, stopping knowledge leakage.
Additionally they carried out difficulty-based response filtering utilizing DeepScaleR-1.5B-Preview, finally forming a 76,000-example dataset for the primary stage of supervised fine-tuning. A second, tougher dataset of three,000 examples additional improved efficiency.
After coaching, the group merged a number of educated variations of Gentle-R1-32B, resulting in extra features. Notably, the mannequin maintains sturdy generalization skills on scientific reasoning duties (GPQA), regardless of being math-specialized.
How enterprises can profit
Gentle-R1-32B is launched beneath the Apache License 2.0, a permissive open-source license that enables free use, modification, and business deployment with out requiring by-product works to be open-sourced. T
his makes it a gorgeous possibility for enterprises, AI builders, and software program engineers seeking to combine or customise the mannequin for proprietary purposes.
The license additionally features a royalty-free, worldwide patent grant, lowering authorized dangers for companies whereas discouraging patent disputes. Firms can freely deploy Gentle-R1-32B in business merchandise, sustaining full management over their improvements whereas benefiting from an open and clear AI ecosystem.
For CEOs, CTOs, and IT leaders, Apache 2.0 ensures price effectivity and vendor independence, eliminating licensing charges and restrictive dependencies on proprietary AI options. AI builders and engineers acquire the flexibleness to fine-tune, combine, and lengthen the mannequin with out limitations, making it ideally suited for specialised math reasoning, analysis, and enterprise AI purposes. Nevertheless, because the license offers no guarantee or legal responsibility protection, organizations ought to conduct their very own safety, compliance, and efficiency assessments earlier than deploying Gentle-R1-32B in important environments.
Transparency in low-cost coaching and optimization for math downside fixing
The researchers emphasize that Gentle-R1-32B offers a validated, cost-effective technique to practice sturdy long-chain-of-thought fashions in specialised domains.
By sharing their methodology, coaching knowledge, and code, they purpose to decrease the associated fee obstacles for high-performance AI growth.
Future work consists of exploring reinforcement studying (RL) to boost the mannequin’s reasoning capabilities additional.