DeepSeek's Flash outpaced its own flagship. The upgrade was post-training, not p

<!-- SC_OFF --><div class="md"><p>The benchmark sheet dropped this morning and people are losing it in the ML community.</p> <p><strong>What DeepSeek R2 scores:</strong><br />

<h1> DeepSeek V4: Million-Token Context That Actually Works </h1> <p>Most long-context models are benchmarks in search of a use case. DeepSeek V4 flips the script—it delivers 1

<h2> The shift to hybrid reasoning architectures </h2> <p>For the past two years, engineering teams building production generative AI systems operated under a rigid architectural

<!-- SC_OFF --><div class="md"><p>DeepSeek just released V4. Pro is 1.6T total with 49B active. Flash is 284B with 13B active. Both MIT licensed, both 1M context.</p> <p><a

<ul> <li> <strong>Book:</strong> <a href="https://www.amazon.com/dp/B0GX2SQ594" rel="noopener noreferrer">System Design Pocket Guide: Interviews</a> </li> <li> <strong>Also by

<!-- SC_OFF --><div class="md"><p>DeepSeek dropped the full V4 paper this week. preview from april was 58 pages, this version adds a lot of technical depth.</p> <p>What stood out

<table> <tr><td> <a href="https://www.reddit.com/r/ChatGPT/comments/1wcbgcy/deepseek_v41_flash_is_out/"> <img alt="DeepSeek V4-1 Flash is out"

<p>If you looked the other way, you may have missed the stealth preview model that was free on OpenRouter.AI and OpenCode.AI, which was branded "ox-alpha", that was making a bit