System hardware requirements for Search-R1
Search-R1, as a reinforcement learning framework for large language model training, has explicit requirements for computing hardware. According to the official documentation, a GPU with at least 24GB of video memory is required to perform model training (professional computing cards such as NVIDIA A100 are recommended). This requirement stems from several technical factors:
- Base LLM parameter magnitude reaches 3 billion (3B) level
- Multiple model instances need to be maintained simultaneously during the reinforcement learning training process
- Vector Computation Overhead in Retrieval Augmented Generation (RAG) Scenarios
The project team provides detailed example runs (NQ dataset) where the full training process typically takes several hours on a platform that meets the hardware conditions. The documentation also emphasizes network connection stability and API effectiveness as additional key factors for successful runs.
This answer comes from the articleSearch-R1: A Tool for Reinforcement Learning to Train Large Models for Search and ReasoningThe
