{"schema_version":"onlylabs.public_signal.v1","title":"LG AI Research (EXAONE) Model: LGAI-EXAONE/EXAONE-Deep-32B","description":"LG AI Research (EXAONE) model signal with public source context, captured evidence pages, related signals, and category-scoped analysis context.","url":"https://onlylabs.fyi/signals/483f04d4-e069-4102-9442-3f36e8bdc9fa","json_url":"https://onlylabs.fyi/signals/483f04d4-e069-4102-9442-3f36e8bdc9fa/signal.json","generated_at":"2026-06-11T02:50:45.010236+00:00","org":{"slug":"lg-ai","name":"LG AI Research (EXAONE)","category":"neolab","category_label":"Neolab","dossier_url":"https://onlylabs.fyi/labs/lg-ai","dossier_json_url":"https://onlylabs.fyi/labs/lg-ai/dossier.json"},"related_urls":{"signal":"https://onlylabs.fyi/signals/483f04d4-e069-4102-9442-3f36e8bdc9fa","signal_json":"https://onlylabs.fyi/signals/483f04d4-e069-4102-9442-3f36e8bdc9fa/signal.json","source":"https://huggingface.co/LGAI-EXAONE/EXAONE-Deep-32B","lab_dossier":"https://onlylabs.fyi/labs/lg-ai","lab_dossier_json":"https://onlylabs.fyi/labs/lg-ai/dossier.json","analysis":"https://onlylabs.fyi/analysis/lg-ai","analysis_json":"https://onlylabs.fyi/analysis/lg-ai/analysis.json","analysis_evidence_json":"https://onlylabs.fyi/analysis/lg-ai/evidence.json","category":"https://onlylabs.fyi/neolabs","category_json":"https://onlylabs.fyi/neolabs.json","category_feed":"https://onlylabs.fyi/neolabs/feed.xml","category_signals_json":"https://onlylabs.fyi/signals.json?category=neolab","topic":"https://onlylabs.fyi/topics/releases","topic_signals_json":"https://onlylabs.fyi/topics/releases/signals.json?category=neolab","topic_feed":"https://onlylabs.fyi/topics/releases/feed.xml?category=neolab","data_business":null},"answer_pack":{"answer":"LG AI Research (EXAONE) published LGAI-EXAONE/EXAONE-Deep-32B. 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EXAONE-Deep-32B Introduction We introduce EXAONE Deep, which exhibits superior capabilities in various reasoning tasks including math and coding benchmarks, ranging from 2.4B to 32B parameters developed and released by LG AI Research. Evaluation results show that 1) EXAONE Deep **2.4B** outperforms other models of comparable size, 2) EXAONE Deep **7.8B** outperforms not only open-weight models of comparable scale but also a proprietary reasoning model OpenAI o1-mini, and 3) EXAONE Deep **32B** demonstrates competitive performance against leading open-weight models. For more details, please refer to our [documentation](https://arxiv.org/abs/2503.12524), [blog](https://www.lgresearch.ai/news/view?seq=543) and [GitHub](https://github.com/LG-AI-EXAONE/EXAONE-Deep).


EXAONE-Deep-32B Introduction We introduce EXAONE Deep, which exhibits superior capabilities in various reasoning tasks including math and coding benchmarks, ranging from 2.4B to 32B parameters developed and released by LG AI Research. Evaluation results show that 1) EXAONE Deep **2.4B** outperforms other models of comparable size, 2) EXAONE Deep **7.8B** outperforms not only open-weight models of comparable scale but also a proprietary reasoning model OpenAI o1-mini, and 3) EXAONE Deep **32B** demonstrates competitive performance against leading open-weight models. For more details, please refer to our [documentation](https://arxiv.org/abs/2503.12524), [blog](https://www.lgresearch.ai/news/view?seq=543) and [GitHub](https://github.com/LG-AI-EXAONE/EXAONE-Deep).