NVIDIA Announces B300 GPU for Next-Gen AI Training
NVIDIA has unveiled the B300 GPU, featuring 288GB of HBM4 memory and 2.5x the AI training performance of the H100. The chip will be available through major cloud providers starting Q3 2026.
NVIDIA has announced the B300, its next-generation GPU designed for AI training and inference workloads. The chip features 288GB of HBM4 memory — a 50% increase over the B200 — and delivers 2.5x the training throughput of the H100 for large language model workloads.
The B300 introduces NVIDIA's new Blackwell Ultra architecture, which includes dedicated transformer engines optimized for attention mechanism computation and a new sparsity format that allows models to be trained with 40% fewer FLOPs without accuracy loss. CEO Jensen Huang presented the chip at a special event in Las Vegas, calling it "the engine that will power the next generation of AI."
For inference, the B300 offers particular improvements. New INT4 and FP4 execution units enable serving large models at significantly reduced cost, with NVIDIA claiming a 4x improvement in tokens-per-watt compared to the H100. This addresses a critical industry concern as AI companies face mounting infrastructure costs from serving millions of users.
Major cloud providers including AWS, Azure, Google Cloud, and Oracle have already placed orders for B300 clusters, with initial availability expected in Q3 2026. NVIDIA also announced a new DGX B300 system containing eight B300 GPUs with 2.3TB of combined HBM4 memory, designed for training models with hundreds of billions of parameters.
The B300 is priced at approximately $40,000 per unit, roughly 30% more than the B200. Despite the premium, demand is expected to far exceed supply for the first several quarters, continuing the pattern of GPU scarcity that has characterized the AI boom.
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