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DeepSeek, Reasoning Models, and the Future of LLMs

Guido Appenzeller, Marco Mascorro

DeepSeek R1 is an open-weight reasoning model from China that achieves top-tier performance by combining Multi-Head Latent Attention, Group Relative Policy Optimization, and a 256-expert MoE architecture to generate complex thought chains. The development team overcame early behavioral failures through a low-cost, self-supervised pipeline utilizing 800,000 verifiable traces and rule-based verification to produce responses up to 10,000 tokens long for roughly $5.5 million in base training costs. This breakthrough has shifted industry focus toward test-time compute and local deployment, enabling state-of-the-art reasoning on consumer hardware while bypassing traditional bottlenecks associated with human-labeled data.