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**FrontierMath Tier 4** results show **GPT-5 Pro** narrowly outperforming **Gemini 2.5 Deep Think** in reasoning accuracy, with concerns about problem leakage clarified by **Epoch AI Research**. **Mila** and **Microsoft** propose **Markovian Thinking** to improve reasoning efficiency, enabling models to reason over 24K tokens with less compute. New research suggests base models inherently contain reasoning mechanisms, with "thinking models" learning to invoke them effectively. In systems, **NVIDIA Blackwell** combined with **vLLM** wins InferenceMAX with significant throughput gains, while **Together AI's ATLAS** adaptive speculative decoding achieves 4× speed improvements and reduces RL training time by over 60%. **SparseServe** introduces dynamic sparse attention with KV tiering, drastically improving throughput and latency in GPU memory management.
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