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Stable Diffusion XL NVIDIA TensorRT performance improvement

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Stable Diffusion XL NVIDIA TensorRT performance improvement

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Stable Diffusion XL NVIDIA TensorRT performance improvement

In a new collaboration, Stability AI and NVIDIA have joined forces to supercharge the performance of Stability AI’s text-to-image generative AI product, Stable Diffusion XL (SDXL). This partnership is set to revolutionize the speed and efficiency of SDXL, bringing Stability AI a step closer to its ambitious mission of unlocking humanity’s potential.

The secret sauce behind this performance upgrade is the integration of NVIDIA TensorRT, a high-performance optimization framework. This powerful tool will be hosted by Stability AI, with the TensorRT versions of SDXL and the open ONNX weights made available to users worldwide.

The results of this integration have been nothing short of impressive. The marriage of TensorRT and the converted ONNX model has led to a doubling of performance on NVIDIA H100 chips. This means that high-definition images can now be generated in a mere 1.47 seconds.

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Stable Diffusion XL NVIDIA TensorRT

“The Stability AI team is proud to announce a collaboration with NVIDIA that will significantly enhance the speed of our popular text-to-image generative AI product, Stable Diffusion XL. This marks a substantial improvement in the speed and efficiency of our SDXL, thereby drawing us closer to our mission of building the foundation to activate humanity’s potential.

The key to this success is the integration of NVIDIA TensorRT, a high-performance, state-of-the-art performance optimization framework. We are proud to host the TensorRT versions of SDXL and make the open ONNX weights available to users of SDXL globally.

SDXL performance optimizations

But the improvements don’t stop there. Further optimizations, such as the introduction of 8-bit precision, are expected to further boost both speed and accessibility. Performance benchmarks have already shown that the NVIDIA TensorRT-optimized model outperforms the baseline (non-optimized) model on A10, A100, and H100 GPU accelerators.

See also  How to use Stable Diffusion and ControlNet to customize AI images

This speed improvement has far-reaching implications for the democratization of generative AI. By making it faster, more accessible, and more affordable, this collaboration is opening up new possibilities for creators, researchers, and innovators to explore the frontiers of AI-powered applications.

In essence, Stability AI and NVIDIA are working in tandem to train and run models as swiftly as possible. This accelerates their respective missions of activating humanity’s potential and making a positive impact through technology and innovation. This collaboration is a testament to the power of partnership and the limitless possibilities of AI.

Source: Stability

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