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Industry news, technical articles, and product introductions
📚 Claude Tutorials Hub
40+ step-by-step Claude guides — prompt engineering, Claude Code, API, agents. Browse by topic →
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DeepSeek-V4-Pro-0813 posted a Terminal-Bench score 0.1 behind Fable 5, then scored 53 on Artificial Analysis — one point above its own small model — before the announcement vanished that afternoon. The Hugging Face commit log tells a different story than 'the model is bad.'
Netlify ran the same coffee-shop prompt through 11 frontier models using its open-sourced AXIS framework. Credit spend ranged from 2.4 to 519 — and the price tag turned out to be the least interesting part.
Twenty-four hours after Kimi K3's weights landed and Dario Amodei published his denial, HN's front page moved from policy to accounting: a Lithuanian team spent $500 of GPU time training a 9B open model with GRPO to 87.3% on catalog review — beating GPT-5.5, Gemini 3.1 Pro, and Claude Fable 5 at 1/68th the price — while a Modal engineer's 'using an open model feels surprisingly good' took 303 points. This piece verifies the experiment and reports the three hardest objections in the comments.
In a rare 4-hour investor meeting, DeepSeek founder Liang Wenfeng shared the company's founding vision, open-source strategy, API pricing logic, AGI roadmap, organizational philosophy, and views on the China-US AI gap. Here are 10 key insights distilled from the conversation.