StoryFirst seen
Compression cuts the cost of running agents that read far more than they write, where memory overhead has been a core expense.
Everything it touches
1 names 1 voices 1 source posts
The story’s neighborhood
Explore the graph, or choose a connection below.
Follow the evidence
This brief comes from Tech Twitter’s edited headlines. The posts below are the sources grouped with the story; statements in them belong to their authors.
Agents read more than they write, so DeepSeek shrank what they remember. Read the technical breakdown in this week's issue of The Batch. 📰🗜️ 📉 890 bytes of cache per token, 437x smaller than DeepSeek-V1 ⚡ +25% compute per output token from 4K to 1M input 🏆 Flash beats V4-Pro: 39 vs 36 on AA Index, $0.27 vs $0.67/task #DeepLearningAI #LLMs #AIAgentsRead original on X
DeepSeek ships a model with drastically smaller agent memory
DeepSeek ships a model with drastically smaller agent memory
Shared connections
The update is already live across major inference providers, keeping price pressure on in the open-model race.
Attribution of last week's breaches to a single operator using open-source hacking tools and several frontier models resets assumptions about how much damage one person with AI can
The agent gets desktop printer access and pulls calendar, X, and workout data to produce a printed day plan.
Early previews score 38 on the AA intelligence index, and OpenRouter lists API pricing at $0.68 per million input tokens.