genevaquant/Hermes-4-70B-u

Hermes 4 70B: A Frontier Reasoning Model

Hermes 4 70B, developed by Nous Research, is a 70 billion parameter model built on Llama-3.1. It introduces a hybrid reasoning mode that allows the model to deliberate internally using <think>…</think> segments before generating a response, enhancing its problem-solving capabilities. The model's training involved a significantly expanded post-training corpus of approximately 5 million samples and 60 billion tokens, blending reasoning and non-reasoning data.

Key Capabilities

• Advanced Reasoning: Demonstrates massive improvements across math, code, STEM, logic, and creative writing tasks.
• Structured Outputs: Trained to produce valid JSON for given schemas and to repair malformed objects, making it highly suitable for structured data generation.
• Enhanced Steerability: Offers extreme improvements in steerability, notably reducing refusal rates and aligning with user values, as evidenced by its performance on the RefusalBench benchmark.
• Function Calling & Tool Use: Supports function/tool calls within a single assistant turn, integrating them after its internal reasoning process.

When to Use This Model

• Complex Problem Solving: Ideal for applications requiring deep reasoning, logical deduction, and multi-step problem-solving.
• Structured Data Generation: Excellent for tasks needing precise, format-faithful outputs like JSON generation or schema adherence.
• Creative and Technical Content: Suitable for generating high-quality content in creative writing, coding, and STEM fields.
• Applications Requiring Alignment: When a model needs to be highly steerable and conform to specific user values without unnecessary refusals.