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Infra2026-08-08 · source-backed
The Hrazdan facility opened August 8, scaling to 300 megawatts and 70,000+ NVIDIA Rubin and Blackwell GPUs by end of 2027, built on NVIDIA DSX (40% more GPUs on the same footprint) with Dell PowerEdge, Schneider Electric power and Vertiv cooling. NVIDIA intends to invest, following CoreWeave's earlier stake. Perplexity is already a compute customer as part of a 2-gigawatt roadmap across Armenia and Kazakhstan. Six months from nothing to CIS-largest is the number to sit with.
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NVHBM, announced August 26, relocates NVIDIA's custom memory controller from the compute chip into the HBM base die, claiming up to 30% more bandwidth than standard HBM4E, 15% lower HBM power, and up to 25% more freed area on the XPU compute die (NVIDIA). Next-generation Train...
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'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 —...
Portable Computer launched August 26, running the orchestrator LLM, subagent LLM, planner, tool router, scheduler and local search index locally, with local work consuming no billing credits and each cloud escalation requiring separate approval (VentureBeat). Launch platform i...
The argument is that AI rack density outgrew AC distribution, and 800-volt DC cuts conversion stages between grid and GPU so more available power reaches compute (NVIDIA). Staged rollout: hybrid AC-compatible power rack in H2 2026, row power center supporting up to 2 MW per ro...
Announced at FMS, the cuFile APIs let GPUs read and write storage directly in microseconds rather than routing through CPUs, and SCADA (scaled, accelerated data access) lets massively parallel GPUs pull only application-necessary data into high-bandwidth memory. NVIDIA also sh...
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