MODEL PROFILE

EXAONE-Deep-7.8B

LGAI-EXAONE · EXAONE-Deep-7.8B

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. > ### Note > The EXAONE Deep models are trained with an optimized configuration, > so we recommend following the Usage Guideline section to achieve optimal performance. The following table shows the evaluation results of reasoning tasks such as math and coding. The full evaluation results can be found in the documentation.

Text generationlicense:other
Context window32,768 Token
Input → OutputText → Text
Model weightsNot verified
Profile updated2026/11/2 19:17:16
OVERVIEW

Model overview

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. > ### Note > The EXAONE Deep models are trained with an optimized configuration, > so we recommend following the Usage Guideline section to achieve optimal performance. The following table shows the evaluation results of reasoning tasks such as math and coding. The full evaluation results can be found in the documentation.

Key features

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Limitations & considerations

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PRICING & COST

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INDEPENDENT BENCHMARKS

Public benchmarks & run configuration

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Frequently asked questions

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Sources & traceability

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