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nousresearch_hermes-4-14b
Hermes 4 14B is a frontier, hybrid-mode reasoning model based on Qwen 3 14B by Nous Research that is aligned to you. Read the Hermes 4 technical report here: Hermes 4 Technical Report Chat with Hermes in Nous Chat: https://chat.nousresearch.com Training highlights include a newly synthesized post-training corpus emphasizing verified reasoning traces, massive improvements in math, code, STEM, logic, creativity, and format-faithful outputs, while preserving general assistant quality and broadly neutral alignment. What’s new vs Hermes 3 Post-training corpus: Massively increased dataset size from 1M samples and 1.2B tokens to ~5M samples / ~60B tokens blended across reasoning and non-reasoning data. Hybrid reasoning mode with explicit … segments when the model decides to deliberate, and options to make your responses faster when you want. Reasoning that is top quality, expressive, improves math, code, STEM, logic, and even creative writing and subjective responses. Schema adherence & structured outputs: trained to produce valid JSON for given schemas and to repair malformed objects. Much easier to steer and align: extreme improvements on steerability, especially on reduced refusal rates.

Repository: localaiLicense: apache-2.0

nousresearch_hermes-4-70b
Hermes 4 70B is a frontier, hybrid-mode reasoning model based on Llama-3.1-70B by Nous Research that is aligned to you. Read the Hermes 4 technical report here: Hermes 4 Technical Report Chat with Hermes in Nous Chat: https://chat.nousresearch.com Training highlights include a newly synthesized post-training corpus emphasizing verified reasoning traces, massive improvements in math, code, STEM, logic, creativity, and format-faithful outputs, while preserving general assistant quality and broadly neutral alignment. What’s new vs Hermes 3 Post-training corpus: Massively increased dataset size from 1M samples and 1.2B tokens to ~5M samples / ~60B tokens blended across reasoning and non-reasoning data. Hybrid reasoning mode with explicit … segments when the model decides to deliberate, and options to make your responses faster when you want. Reasoning that is top quality, expressive, improves math, code, STEM, logic, and even creative writing and subjective responses. Schema adherence & structured outputs: trained to produce valid JSON for given schemas and to repair malformed objects. Much easier to steer and align: extreme improvements on steerability, especially on reduced refusal rates.

Repository: localaiLicense: llama3