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Home»ADOPTION NEWS»NVIDIA’s FP4 Image Creation RTX 50 Series GPU performance improvement
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NVIDIA’s FP4 Image Creation RTX 50 Series GPU performance improvement

By Crypto FlexsMay 18, 20253 Mins Read
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NVIDIA’s FP4 Image Creation RTX 50 Series GPU performance improvement
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Terryl Diki
May 14, 2025 07:53

NVIDIA’s latest Tens1 update introduces the FP4 image of the RTX 50 series GPU to improve AI model performance and efficiency. Explore the development of created AI technology.





NVIDIA unveiled a significant leap of AI technology with the launch of the Blackwell platform featuring the new GeForce RTX 50 Series GPU. According to NVIDIA, this GPU is equipped with a 5th -generation tensor core that supports a 4 -bit plotting point computing (FP4), and according to NVIDIA, important development for accelerating the sophisticated AI model.

FP4 quantification and model optimization

The FP4 quantization technology is designed to improve the performance and quality of the image creation model that is increasingly required in terms of speed, resolution and complexity. NVIDIA’s Tens1 software ecosystem supports FP4 quantification to provide a library that facilitates local reasoning distribution to PCs and workstations. This shows significant changes in the existing 16 -bit and 8 -bit computing mode.

NVIDIA has successfully quantified the flux model with FP4 weight using advanced post -training quantification (PTQ) and quantization recognition training (QAT) technology. This approach is especially fine in detail, which reduces the initial image quality decrease and improved the evaluation metrics through micro -adjustment with synthetic data.

Export and distribution

For efficient distribution, the FP4 model is exposed in the ONNX format, so it is possible to accurately define the input/output tensor and the offline quantitative weight tensor. The export process includes a combination of standard onnx dequantization nodes and Tens1 custom operators to maintain numerical stability.

The placement of such a model is further simplified by the ability of TensRT to handle quantified operators, facilitating the end -to -end reasoning journey. Integration with comfyui, a popular image creation tool, allows users to use high -quality flux pipelines using the optimized tens1 engine of NVIDIA.

FP4 performance development

The introduction of FP4 to NVIDIA’s BLACKWELL GPU has some advantages, including increased mathematical throughput and memory footprints compared to FP32 and FP8. The FP4 data type also ensures superior reasoning accuracy compared to INT4, which optimizes performance while maintaining work accuracy.

In a practical point of view, the flux pipeline is especially up to 3.1 times the performance compared to the FP8 by showing significant performance benefits with FP4 inferences, especially in the completely connected layer of the transformer model. This performance improvement is important for efficiently running large models on consumer desktops.

Influence and future prospects

The development of FP4 image creation emphasizes the promise of NVIDIA to raise the boundary of AI technology. NVIDIA enables powerful AI functions in consumer grade hardware, democratizing access to high -end AI tools, and packing methods for innovative applications in various fields.

As the FP4 is integrated into the Tens1.8 Release, NVIDIA continues to lead AI hardware and software innovation, and provides developers and researchers with a powerful tool for exploring new Frontier in AI -centered image creation.

Image Source: Shutter Stock


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