The NVIDIA RTX 4060 Ti 8GB is an excellent GPU for running the CLIP ViT-H/14 vision model. The primary factor determining compatibility is VRAM, and the RTX 4060 Ti's 8GB of GDDR6 VRAM significantly exceeds the 2.0GB required by the model in FP16 precision. This leaves a substantial 6GB VRAM headroom, allowing for comfortable operation even with larger batch sizes or when running other applications concurrently. Furthermore, the Ada Lovelace architecture provides strong support for FP16 operations and tensor cores, which are leveraged by CLIP for efficient computation. The 288 GB/s memory bandwidth, while not the highest available, is sufficient for this model's size and complexity, preventing memory bottlenecks during inference.
To maximize performance with CLIP ViT-H/14 on the RTX 4060 Ti, start with a batch size around 30, which is well within the VRAM limits. While FP16 precision is a good starting point, explore using TensorRT for optimized inference. TensorRT can further accelerate the model by applying graph optimizations and quantization techniques. Experiment with different batch sizes to find the optimal balance between throughput and latency for your specific application. Monitor GPU utilization and memory usage to ensure you're not hitting any bottlenecks.