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Top 5 AI Model Optimization Techniques for Faster, Smarter Inference

As AI models get larger and architectures more complex, researchers and engineers are continuously finding new techniques to optimize the performance and...

As AI models get larger and architectures more complex, researchers and engineers are continuously finding new techniques to optimize the performance and overall cost of bringing AI systems to production. Model optimization is a category of techniques focused on addressing inference service efficiency. These techniques represent the best β€œbang for buck” opportunities to optimize cost…

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Optimizing Inference for Long Context and Large Batch Sizes with NVFP4 KV Cache

Quantization is one of the strongest levers for large-scale inference. By reducing the precision of weights, activations, and KV cache, we can reduce the memory...

Quantization is one of the strongest levers for large-scale inference. By reducing the precision of weights, activations, and KV cache, we can reduce the memory footprint and compute costβ€”directly improving throughput, latency, and achievable context length. This blog introduces NVFP4 KV cache quantization, a new KV format that enables significant performance gains on NVIDIA Blackwell GPUs.

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