DeepSeek's V3: Beating Benchmarks on a Budget

DeepSeek's new V3 model, trained on a mere 2,048 H800 GPUs—a fraction of the resources used by giants like OpenAI—matches or surpasses GPT-4 and Claude on several benchmarks. Their $5.5M training cost dwarfs the estimated $40M for GPT-4. This success, partly driven by US export controls limiting access to high-end GPUs, highlights the potential for architectural innovation and algorithmic optimization over sheer compute power. It's a compelling argument that resource constraints can, paradoxically, spur groundbreaking advancements in AI development.