The NVIDIA RTX 3080 12GB is an excellent GPU for running the CLIP ViT-L/14 vision model. The RTX 3080 boasts 12GB of GDDR6X VRAM, which is significantly more than the 1.5GB required by the CLIP ViT-L/14 model in FP16 precision. This leaves a substantial 10.5GB VRAM headroom, allowing for larger batch sizes, concurrent execution of other tasks, or experimentation with larger models. Furthermore, the RTX 3080's Ampere architecture, featuring 8960 CUDA cores and 280 Tensor Cores, provides ample computational power for accelerating the matrix multiplications and other operations inherent in the CLIP model. The high memory bandwidth of 0.91 TB/s ensures that data can be transferred quickly between the GPU and memory, minimizing bottlenecks during inference.
For optimal performance with the CLIP ViT-L/14 model on the RTX 3080, start with a batch size of 32. Monitor GPU utilization and memory usage; you may be able to increase the batch size further without exceeding VRAM limits. Consider using mixed precision (FP16) inference to reduce memory footprint and potentially improve throughput. Explore using TensorRT or other optimization libraries to further accelerate inference. If you encounter memory issues, reduce the batch size or consider using quantization techniques like INT8, although this may slightly impact accuracy.