The AI Models That Will Replace GPT-5: What You Need to Know About DeepSeek-R1 & o3-mini

Author(s): Tarun Singh

Originally published on Towards AI.

Why the future of AI isn’t bigger models — it’s smarter reasoning.

TL;DR: Reasoning models are the next jump after “just bigger LLMs.” Instead of prompt tricks, they win with reinforcement learning on verifiable tasks, test-time compute, and distillation. In this article you’ll (1) understand the shift, (2) see exactly when reasoning models beat classic LLMs, and (3) get a copy-paste Python pipeline: generate verifiable math/coding tasks, train a tiny RL loop with programmatic rewards, evaluate with pass@k, and serve locally with vLLM + quantization. If you want fast, cheap, and practical reasoning — read on.

The article discusses the evolution of AI, emphasizing that the future lies not simply in larger models but in smarter reasoning capabilities. It explores the advantages of new reasoning models, showcasing how techniques like reinforcement learning on verifiable tasks and strategic test-time computing improve efficiency and effectiveness. The text further outlines the practical steps for implementing these models, highlighting the transition from traditional large language models to innovative, smaller yet powerful models like DeepSeek-R1 and o3-mini, which exemplify this shift in focus.

Read the full blog for free on Medium.

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Published via Towards AI