EduQwen 32B-RL1, EduQwen 32B-SFT, and EduQwen 32B-SFT-RL2

Product or Programme · All products and programmes
Evidence · 2 claims (2 for) · 1 study (1 design), q2 · 0 of 1 report an effect size · 2 claims rest on one study

Description

Singh et al.'s EduQwen family comprises open-source 32-billion-parameter pedagogical LLMs designed for customizable, auditable tutoring and educational-platform integration.

Components

Claims

• The EduQwen 32B models achieve up to 96.52% accuracy on the CDPK Benchmark, surpassing the previous leaderboard leader Gemini-3 Pro at 90.55% [+M]
• The domain-specialized 32-billion-parameter model surpasses significantly larger general-purpose models such as Qwen3-235B-A22B-Thinking (86.63%) and Qwen2.5-72B-Instruct (78.60%) on the CDPK Benchmark [+W]

Related Products and Programmes

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Key Sources

• Singh, N. P., Wang, X., Garikipati, A., Ciobanu, M., Mao, Q., & Das, R. (2026). Application-Driven Pedagogical Knowledge Optimization of Open-Source LLMs via Reinforcement Learning and Supervised Fine-Tuning. Preprint. https://arxiv.org/abs/2604.06385. doi:10.48550/arxiv.2604.06385

Page metadata

Field	Value
type	product
id	eduqwen-32b-rl1-eduqwen-32b-sft-and-eduqwen-32b-sft-rl2
title	EduQwen 32B-RL1, EduQwen 32B-SFT, and EduQwen 32B-SFT-RL2
description	Singh et al.'s EduQwen family comprises open-source 32-billion-parameter pedagogical LLMs designed for customizable, auditable tutoring and educational-platform integration.
status	review
product_kind	software
generated	by process:settle-candidates on 2026-10-11
trust	unverified — no one has confirmed this page's content

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