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Top 5 · 2026-02-22 · source-backed
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 — hits 30 petaFLOPS with 128GB GDDR7 and 3x attention acceleration. Cursor and Magic are named launch partners. Availability H2 2026 via AWS, Google Cloud, Microsoft, CoreWeave. Builder takeaway: This is what makes 1M+ context windows affordable for everyone. Plan your architecture accordingly. NVIDIA
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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 partl...
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
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...
Meta Compute will sell excess AI compute and model access against AWS, Azure, and Google Cloud, backed by up to roughly $145B in 2026 infrastructure spend. CoreWeave shares fell 14% on July 8 as the market read Meta as a credible neocloud threat. For anyone renting GPUs, anoth...
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...
PR #19378 landed in llama.cpp this week, and I think most people are underselling what it means. Backend-agnostic tensor parallelism via --split-mode tensor makes multi-GPU inference work across AMD, Intel, and Apple Silicon. Not just CUDA. Everything. For context: llama.cpp h...
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