TurboOCR achieves 270–1200 img/s OCR by optimizing PaddleOCR with C++/CUDA, FP16 TensorRT, fused kernels, and batched processing, addressing the performance bottlenecks of VLM-based approaches. This solution drastically improves throughput for large-scale document processing and is suitable for real-time RAG applications.
This article details deploying Llama 3.2 Vision with TensorRT on a DigitalOcean GPU Droplet, achieving 3.5x faster multimodal inference at 1/95th the cost of GPT-4 Vision. It aims to empower developers to optimize costs and performance for open-source models, avoiding expensive APIs and slow local inference.
This article introduces ComfyUI-TensorRT-Reforge, a new custom node for ComfyUI that accelerates AI model inference with TensorRT, enabling the use of LoRAs. It solves the problem of slow image generation and the limitations of existing solutions, combining speed and flexibility.