{"slug":"hermes-4-405b","id":"hermes-4-405b","type":"model","title":"Hermes 4 405B","description":"Nous Research's flagship open-weight model with hybrid reasoning (toggle between standard and explicit chain-of-thought with think tags). Based on Llama 3.1, trained with rejection sampling via 1,000+ task verifiers. Known for minimal content restrictions and user-directed behavior.","last_updated":"2026-04-10","last_verified":null,"verification_status":"unverified","markdown_url":"/content/models/hermes-4-405b.md","html_url":"/models/hermes-4-405b","api_url":"/api/v1/models/hermes-4-405b.json","content_hash":"faba518cd7a696af5fb5455cefb68fe5c879d8df7eeb18cf4777d03b1088f819","sha256":"faba518cd7a696af5fb5455cefb68fe5c879d8df7eeb18cf4777d03b1088f819","provider":"Nous Research","pricing":{"input":"Free (self-hosted)","output":"Free (self-hosted)","free":true,"note":"Or via Nous Portal / OpenRouter"},"benchmarks":{"reasoning":88,"coding":84,"math":90,"writing":85,"multilingual":78,"speed":55},"tags":["nous research","open-source","text"],"website":"https://nousresearch.com","release_date":"2025-08","relationships":{"links":[],"related":[{"id":"cohere-tiny-aya","title":"Cohere Tiny Aya 3.35B","type":"model","html_url":"/models/cohere-tiny-aya","markdown_url":"/content/models/cohere-tiny-aya.md","shared_tags":["open-source","text"],"score":4},{"id":"command-r-plus","title":"Command R+","type":"model","html_url":"/models/command-r-plus","markdown_url":"/content/models/command-r-plus.md","shared_tags":["open-source","text"],"score":4},{"id":"deepseek-r1","title":"DeepSeek R1","type":"model","html_url":"/models/deepseek-r1","markdown_url":"/content/models/deepseek-r1.md","shared_tags":["open-source","text"],"score":4},{"id":"deepseek-v3.2","title":"DeepSeek V3.2","type":"model","html_url":"/models/deepseek-v3.2","markdown_url":"/content/models/deepseek-v3.2.md","shared_tags":["open-source","text"],"score":4},{"id":"falcon-3","title":"Falcon 3","type":"model","html_url":"/models/falcon-3","markdown_url":"/content/models/falcon-3.md","shared_tags":["open-source","text"],"score":4},{"id":"gemma-3","title":"Gemma 3","type":"model","html_url":"/models/gemma-3","markdown_url":"/content/models/gemma-3.md","shared_tags":["open-source","text"],"score":4}],"explicit":{}},"metadata":{"title":"Hermes 4 405B","type":"model","id":"hermes-4-405b","provider":"Nous Research","model_type":"open-source","release_date":"2025-08","description":"Nous Research's flagship open-weight model with hybrid reasoning (toggle between standard and explicit chain-of-thought with think tags). Based on Llama 3.1, trained with rejection sampling via 1,000+ task verifiers. Known for minimal content restrictions and user-directed behavior.","last_updated":"2026-04-10","context_window":"128K tokens","website":"https://nousresearch.com","license":"Llama Community License","modality":["text"],"tags":["nous research","open-source","text"],"pricing":{"input":"Free (self-hosted)","output":"Free (self-hosted)","free":true,"note":"Or via Nous Portal / OpenRouter"},"benchmarks":{"reasoning":88,"coding":84,"math":90,"writing":85,"multilingual":78,"speed":55},"parameters":"405B (also available in 14B, 70B)","hardware_requirements":"4x A100 80GB (FP16); 2x RTX 4090 with Q4 quantization","best_for":["Uncensored use cases","Research","Hybrid reasoning experiments","Fine-tuning"]},"content_text":"# Hermes 4 405B\n\nThe model for people who want minimal guardrails and maximum steerability. Hermes 4 is Nous Research's fine-tune of Llama 3.1, trained with rejection sampling across 1,000+ task verifiers, and it comes with the least restrictive content policy of any major open-weight model. If you need a model that does what you tell it without second-guessing, this is it.\n\nThe math performance is the headline benchmark: 96.3% on MATH-500 and a 90/100 math score put Hermes in rare territory for an open model. The hybrid reasoning toggle -- switch between standard generation and explicit chain-of-thought via think tags -- gives you control over the quality/speed tradeoff on a per-query basis. Reasoning at 88/100 is competitive with DeepSeek V3.2 and Qwen 3.\n\nThe downsides reflect the Llama 3.1 base. At 405B dense parameters, this model is heavy -- 4x A100 80GB for FP16 -- and the speed score of 55/100 is the slowest of any model on this list except DeepSeek R1. Multilingual support at 78/100 is weak compared to Qwen 3 (95) or Mistral 3 (92). The community, while passionate, is a fraction of Llama's or Qwen's.\n\n**When to pick something else:** For coding, Qwen 3 (90/100) and DeepSeek V3.2 (88/100) are stronger. For general reasoning at lower hardware cost, Llama 4 Maverick's MoE architecture is more efficient. Hermes 4's niche is clear: uncensored, highly steerable, math-strong open weights for researchers and developers who want to push boundaries without content restrictions.","content_length":2583,"generated_at":"2026-04-24"}