In order to fully utilize the performance of DeepCoder-14B-Preview's 14 billion parameter model, it is officially recommended to use NVIDIA GPUs configured with more than 24GB of video memory, and specific hardware requirements include:
- Best configuration: NVIDIA H100 and other professional computing cards
- Minimum Requirements: RTX 3090/4090 and other consumer graphics cards
- CPU mode requires at least 128GB of RAM
Complete runtime environment configuration program:
- Python 3.10 environment (isolation via conda recommended)
- Must depend on libraries: transformers, torch, vllm, etc.
- CUDA 11.8 or above is recommended
Reasoning on H100 has been proven to be as fast as 45 token/s, and the 24GB video memory card ensures stable operation in 32K contexts. CPU offload mode will be enabled automatically when there is not enough video memory, but the speed will drop above 80%.
This answer comes from the articleDeepCoder-14B-Preview: an open source model that specializes in code generationThe
May not be reproduced without permission:AI productivity tools " 24GB video memory GPU is the recommended hardware configuration for running DeepCoder-14B-Preview
