Nous Research unveils DeepHermes-3, an AI model that unifies reasoning and intuitive language capabilities, allowing users to toggle between different modes for various applications. Learn more about this personalized, unrestricted AI.
AI reasoning models, which generate “chains-of-thought” (CoT) in text and analyze their own work to catch errors, are gaining traction. Nous Research, a collective focused on creating “personalized, unrestricted” AI models, has introduced DeepHermes-3 Preview. This model allows users to switch between longer reasoning processes and shorter, faster responses.
DeepHermes-3 is described as a large language model (LLM) that unifies reasoning and intuitive language model capabilities. According to Nous Research, the model allows the user to switch between longer reasoning processes and shorter, faster, less computationally demanding responses. It is an 8-billion parameter variant of Hermes 3, itself a variant of Meta’s Llama.
Nous wrote that its researchers “hope our unique approach to user controlled, toggleable reasoning mode furthers our mission of giving those who use DeepHermes more steerability for whatever need they have.”
DeepHermes-3 builds upon the Hermes 3 dataset, a collection used for the broader Hermes 3 series. According to the Hermes 3 Technical Report, this dataset contains approximately 390 million tokens across various domains.
The dataset includes:
Users can manage DeepHermes-3’s reasoning depth using a system prompt. To activate reasoning mode, the following text must be entered before a prompt:
“You are a deep thinking AI, you may use extremely long chains of thought to deeply consider the problem and deliberate with yourself via systematic reasoning processes to help come to a correct solution prior to answering. You should enclose your thoughts and internal monologue inside tags, and then provide your solution or response to the problem.“
When enabled, the model uses long CoTs, marked by <think></think> tags, to structure its internal monologue before providing a solution. In standard response mode, the model provides quicker, intuition-based answers.
Early testing shows:
Nous Research is actively collecting user feedback to improve the model.
DeepHermes-3 is based on Meta’s Llama 3 and is subject to the Meta Llama 3 Community License. This license allows free use, modification, and redistribution, but with conditions:
Users can download the full model code on HuggingFace and a version that’s been quantized (reduced bit count) and saved in the GPT-generated unified format (GGUF), which is designed to run model inferences (the actual production build, as opposed to training) on consumer-grade PCs and servers.
On one hand, it's another AI trying to be smarter than it actually is, like a toddler wearing a graduation cap. Seriously, another toggleable reasoning model? Are we that desperate to mimic human thought processes? But, I'll admit, the idea of switching between quick-fire responses and deep-dive analysis is kind of... smart.
Imagine this: DeepHermes-3 embedded in a legal AI, sifting through mountains of case law in nanoseconds, then switching to 'reasoning mode' to craft airtight arguments, complete with dramatic courtroom flair. Or picture it in a financial modeling tool, crunching numbers like a supercomputer, then toggling to 'intuitive mode' to explain complex market trends to clueless investors in plain English. The potential for disruption is there, but let's be honest, it'll probably end up writing clickbait articles and generating deepfakes.
