# What is Process Reward Model? Definition & Technical Mechanics

> **Source:** [SPIDITS AI AI Glossary](https://spidits.com/ai-glossary)  
> **Category:** Model Training  
> **Canonical Citation:** [https://spidits.com/ai-glossary/process-reward-model](https://spidits.com/ai-glossary/process-reward-model)

## Definition
A Process Reward Model (PRM) is a reward system that scores each individual step or line of reasoning in a model's output, rather than just the final answer. This encourages models to follow correct logical steps and helps prevent hallucinations during complex tasks.

## Architectural Mechanics & Deep Dive
Process Reward Models (PRMs) are reinforcement learning feedback systems trained to evaluate every individual step or line of reasoning in a model's generated thinking chain. By scoring intermediate steps rather than just the final answer, PRMs provide granular alignment signals that discourage hallucinated logic and reward correct reasoning paths. This step-by-step verification is crucial for training complex multi-step reasoning agents.

## Industry Applications & Real-World Use Cases
Mathematical reasoning, software code synthesis, and multi-step theorem proving

## Frequently Asked Questions

### What is the difference between PRM and ORM?
An Outcome Reward Model (ORM) only evaluates the final result, whereas a PRM scores every intermediate step of the model's thinking process.

### Why are PRMs valuable for reasoning models?
They allow reinforcement learning to target exactly where a model made a logical error, leading to better multi-step problem solving.

## Related Terminology
- [outcome-reward-model](https://spidits.com/ai-glossary/outcome-reward-model)
- [reinforcement-learning](https://spidits.com/ai-glossary/reinforcement-learning)
- [chain-of-thought](https://spidits.com/ai-glossary/chain-of-thought)

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*From the SPIDITS AI Knowledge Base (300+ terms indexed). Explore full technical definitions: [https://spidits.com/ai-glossary](https://spidits.com/ai-glossary)*