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State-space models can achieve $1.8\times$ speculative decoding throughput and $1.47\times$ faster standard decoding by caching SSM inputs instead of their full state.
Achieving six times the inference throughput of current LLMs while maintaining accuracy, Nemotron 3 Ultra redefines performance benchmarks for agentic reasoning tasks.
Multimodal models can now achieve state-of-the-art performance in real-world tasks like document understanding and audio-video comprehension with significantly reduced inference latency thanks to novel token-reduction techniques.
