The NVIDIA Jetson AGX Orin 32GB is exceptionally well-suited for running the FLUX.1 Dev model. With 32GB of LPDDR5 VRAM, it comfortably exceeds the model's 24GB FP16 VRAM requirement, leaving a substantial 8GB headroom. This is crucial not only for accommodating the model itself but also for the overhead associated with intermediate calculations during inference, operating system processes, and other concurrently running applications. The Ampere architecture, with its 1792 CUDA cores and 56 Tensor Cores, is designed for efficient parallel processing, which directly benefits the performance of diffusion models like FLUX.1 Dev. While the 210 GB/s memory bandwidth might become a bottleneck for larger batch sizes or more complex models, it's generally sufficient for interactive generation.
Given the ample VRAM headroom, you can experiment with slightly larger batch sizes or higher resolution outputs with FLUX.1 Dev. However, closely monitor VRAM usage to prevent out-of-memory errors. For optimal performance on the Jetson AGX Orin, consider using a framework optimized for NVIDIA GPUs, such as TensorRT or even ONNX Runtime with CUDA execution provider. Additionally, explore techniques like model quantization (e.g., INT8) to further reduce memory footprint and accelerate inference, especially if you plan to run multiple instances or processes concurrently.