DeepSeek V4.1 Flash: KV-cache shrunk to 890 bytes per token
Prompt Engineering · youtube · 2026-09-14
The "Prompt Engineering" channel reviews DeepSeek V4.1 Flash, calling it possibly the best local vision model yet. Its core idea: make long-context AI dramatically more efficient, shrinking KV-cache memory to just 890 bytes per token via architectural changes.
The video covers the efficiency-focused architecture, harness and pricing setup, caching and speed wins, Three.js visual demos, an AutoML training test, and vision benchmarks. The author argues this memory efficiency matters for long-running agents and huge codebases, while noting it still trails frontier systems in places.
The model is open-sourced on Hugging Face (deepseek-ai/DeepSeek-V4.1-Flash) with an official blog post.
Related event: DeepSeek Ships V4.1-Flash, Compressing KV Cache to 890 Bytes per Token(6 posts)→
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