Fetching from the wire…
Infra2026-06-02 · source-backed
Six co-designed chips, supply chain twice the size of Grace Blackwell, with AWS, Google Cloud, Microsoft, and OCI deploying instances in H2 2026 (NVIDIA). If inference really drops 10x, the economics of always-on agents change at the root. The cost crisis in story one is partly a Blackwell-era pricing problem that the next generation is built to undo.
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NVIDIA's next-gen platform comprising seven chips, five rack-scale systems, and a supercomputer purpose-built for agentic AI is now in production. AWS, Google Cloud, Azure, and OCI deploy first in H2 2026. The Vera CPU and BlueField-4 STX storage architecture position it as Bl...
NVIDIA's Blackwell successor is in production ahead of schedule. The NVL72 rack (72 GPUs) delivers 3.6 exaFLOPS for inference, with 288GB HBM4 per GPU. NVIDIA claims 10x lower cost-per-token versus Blackwell. The Rubin CPX variant — purpose-built for million-token inference —...
72-GPU racks with 50 PFLOPS/GPU, 260 TB/s NVLink 6, BlueField-4 AI-native storage for agentic KV-cache sharing. H2 2026 availability from AWS, Google Cloud, Microsoft, CoreWeave, and Nebius. NVIDIA Newsroom
In a July 17 post, NVIDIA pushes "intelligence per dollar" as the agentic-era metric, arguing post-training rather than pretraining is now the central workload because agents need continuous improvement cycles. The claim: a 10-trillion-parameter MoE on 100 trillion tokens in o...
NVIDIA and AWS announced June 23 that NVIDIA's cuVS library now powers GPU-accelerated vector indexing as the default in Amazon OpenSearch Serverless, claiming up to 10x faster index builds at roughly a quarter the cost versus CPU-only, making billion-scale vector DBs buildabl...
Bloomberg reported August 22 that Nvidia notified its largest customers that servers with its AI chips will cost more than 15% more in many cases, driven by memory prices, effective on systems shipped early next year and covering flagship Vera Rubin and Grace Blackwell configu...
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