Explore the latest developments concerning Build with DeepSeek.
Build with DeepSeek V4 Using NVIDIA Blackwell and GPU-Accelerated Endpoints | NVIDIA Technical Blog
DeepSeek just launched its fourth generation of flagship models with DeepSeek-V4-Pro and DeepSeek-V4-Flash, both targeted at enabling highly efficient million-token context inference.
DeepSeek-V4-Pro is the largest model in the family, with 1.6T total parameters and 49B active parameters. DeepSeek-V4-Flash is a smaller 284B-parameter model with 13B active parameters, designed for higher-speed, higher-efficiency workloads. Both models support up to a 1M-token context window, opening new possibilities for long-context coding, document analysis, retrieval, and agentic AI workflows.
The V4 family builds on the DeepSeek MoE architecture, with an increased focus on optimizing the attention component of the transformer architecture. These innovations are designed to achieve a 73% reduction in per-token inference FLOPs and a 90% reduction in KV cache memory burden compared with DeepSeek-V3.2.
DeepSeek V4 is here: How it compares to ChatGPT, Claude, Gemini
That may as well be the motto for the AI arms race, which is unfolding across multiple dimensions in 2026. There's the competition between Silicon Valley AI labs like Anthropic, OpenAI, and Google DeepMind, the race for chips and compute power, and, of course, the fierce competition between the U.S. and China.
In the latest salvo in the East vs. West battle for AI supremacy, Chinese artificial intelligence company DeepSeek has released a preview of its latest model, DeepSeek V4.
Here's what we know about the new model, and how it stacks up against other new models like OpenAI's GPT-5.5 and Anthropic's Claude Opus 4.7.
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