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[[{“value”:”DeepSeek V4.1 Flash is built around one idea: make long-context AI dramatically more efficient. In this video, I break down how DeepSeek shrinks KV-cache memory to just 890 bytes per token, the architectural changes that make it possible, why this matters for long-running agents and huge codebases, and where the model still falls short against frontier systems.
LINKS:
Blogpost: https://www.deepseek.com/en/news/deepseek-v4-1-flash/
Huggingface: https://huggingface.co/deepseek-ai/DeepSeek-V4.1-Flash
ENGRAM: https://youtu.be/zt1jlTPCaps
DSpark: https://youtu.be/eFgknPFK-g0
Flash V4.1 Breakdown: https://youtu.be/nriu4twWHz4
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00:00 DeepSeek V4.1 Flash
01:05 Efficiency and Architecture
01:50 Harness and Pricing Setup
03:27 Caching and Speed Wins
04:23 Three.js Visual Demos
06:20 AutoML Training Test
07:59 Vision Benchmark”}]] Read More Prompt Engineering
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