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DDN announced the AI400X3M appliance at ISC 2026, offering up to 35% higher read throughput than its previous generation and up to 190 GB/sec throughput performance. The company also released distributed KV Cache acceleration technology integrated with NVIDIA Dynamo, along with new security and efficiency tools for large-scale AI deployments.
Why it matters
Organizations scaling from AI pilots to production are struggling with data bottlenecks across the AI pipeline—from training to inference to retrieval and agentic AI. DDN's announcements target these constraints by improving GPU utilization, reducing inference costs, and lowering the cost per token and increasing tokens-per-watt efficiency, directly affecting how much enterprises spend to run AI systems at scale.
What to watch
The AI400X3M can store up to 30 PB in a single rack and supports hybrid disk options, which DDN highlights as important given rising NAND flash costs. The system is designed to reduce power, cooling, and operational costs alongside inference performance gains.
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