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Paper · arXiv 2508.18255

Hermes 4 Technical Report

Ryan Teknium, Roger Jin, Jai Suphavadeeprasit, Dakota Mahan, Jeffrey Quesnelle, Joe Li, Chen Guang, Shannon Sands, Karan Malhotra

57 upvotesAugust 25, 2025arXiv 预印本
AI 摘要

Hermes 4, a hybrid reasoning model, integrates structured multi-turn reasoning with broad instruction-following, evaluated across various benchmarks including math, coding, knowledge, comprehension, and alignment.

hybrid reasoning modelsstructured reasoningmulti-turn reasoninginstruction-followingdata curationdata synthesismodel trainingmodel evaluationmathematical reasoningcodingknowledge benchmarkscomprehension benchmarksalignment benchmarks

Abstract

We present Hermes 4, a family of hybrid reasoning models that combine structured, multi-turn reasoning with broad instruction-following ability. We describe the challenges encountered during data curation, synthesis, training, and evaluation, and outline the solutions employed to address these challenges at scale. We comprehensively evaluate across mathematical reasoning, coding, knowledge, comprehension, and alignment benchmarks, and we report both quantitative performance and qualitative behavioral analysis. To support open research, all model weights are published publicly at https://huggingface.co/collections/NousResearch/hermes-4-collection-68a731bfd452e20816725728

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