Build with DeepSeek V4 Using NVIDIA Blackwell and GPU-Accelerated Endpoints
Build with DeepSeek V4 Using NVIDIA Blackwell and GPU-Accelerated Endpoints | NVIDIA Technical Blog
DeepSeek V4 is introduced as a frontier-scale model built for million-token context reasoning, with both Pro and Flash variants optimized for long-context efficiency. The article explains how its hybrid attention design cuts FLOPs and KV-cache memory, making large-context agent workflows far more practical. NVIDIA highlights Blackwell hardware as the ideal match, with early benchmarks showing strong throughput and perf-per-watt gains. Developers can use DeepSeek V4 immediately through GPU-accelerated endpoints or deploy it via NIM containers for self-hosted setups. The blog also outlines serving options with SGLang and vLLM, tuned for low latency or large-scale inference. Several agentic examples-NemoClaw, AI-Q Blueprint, and Data Explorer Agent-illustrate how the model excels in reasoning and tool-calling. Overall, the article positions DeepSeek V4 as a highly efficient long-context model that reaches its full potential when paired with NVIDIA’s Blackwell‑optimized stack.