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DeepSeek just dropped a new math model that pushes structured reasoning past Gemini 3 DeepThink, hitting Olympiad-tier proof accuracy with a full student–teacher–supervisor loop that checks and corrects its own logic. At the same time, Tencent released HunyuanOCR — a tiny 1 B-parameter expert model that reads documents, receipts, tables, and multilingual pages better than massive vision-language systems built with tens of billions of parameters. These two drops show how fast specialist models are overtaking giant general models in the tasks that actually matter.
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🧠 What You’ll See:
• How DeepSeek Math V2 builds proofs using a student–teacher–supervisor loop
• How self-verification cuts hallucinations and stabilizes chain-of-thought
• How it reaches IMO-level results on proof benchmarks and near-perfect Putnam scores
• How Tencent HunyuanOCR handles long pages, complex layouts, and messy real-world scans
• How its architecture keeps full document shape instead of forcing square crops
• How a 1 B specialist beats huge VLMs on public benchmarks like OmniDocBench, OCRBench, and multilingual tasks
🚨 Why It Matters:
AI is splitting into two directions. Massive all-in-one models keep getting bigger, while small expert systems suddenly outperform them with cleaner outputs, lower latency, and real-world reliability. DeepSeek Math V2 and Tencent HunyuanOCR show how fast focused models are catching up — and in some cases, winning outright.
Sources:
DeepSeek Math V2 on GitHub (with PDF & model files)
https://github.com/deepseek-ai/DeepSeek-Math-V2
DeepSeek Math V2 model card on Hugging Face
https://huggingface.co/deepseek-ai/DeepSeek-Math-V2
Tencent HunyuanOCR technical report
https://arxiv.org/html/2511.19575v1
Coverage of HunyuanOCR on Hugging Face / social media
https://www.facebook.com/0xSojalSec/posts/tencents-released-open-source-hunyuanocr-on-huggingface-ranks-top-on-many-benchm/1383047553349644/
Benchmark discussion referencing OmniDocBench / evaluation context for HunyuanOCR
https://github.com/deepseek-ai/DeepSeek-OCR/issues/281
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