Serving massive context windows is no longer an arithmetic problem.
Once sparse attention reduces compute costs, the absolute limit on agent deployment becomes memory bandwidth and cache capacity. A new paper, "DeepSeek-V4.1-Flash: Pushing the Limits of KV Cache Compression",
Shipped a small geography game this week.
DROPPED Coding: DeepSeek V4 Flash Audit: Nemotron 3 Ultra Design cost = $0 👀 thanks for AntSeed 🐜🐜🐜 try it =
I gave two models the exact same prompt.
Build me a landing page. Fable 5: $1.21 DeepSeek V4.1 Flash: $0.026 That's 46x cheaper. For nearly identical output. The benchmark that actually matters isn't performance. It's performance per dollar. And that gap just got hard to
The usual story is that China just distills U.S. AI models.
Delphi Ventures' Shaughnessy119 says the DeepSeek R1 paper shows real innovation, and that cheap Chinese open source models are exactly why OpenAI and Anthropic want a regulatory moat. 🐉
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