Models & Labs
OpenAI DevDay: Agents, GPT-6.1, and Codex Cloud
Sam Witteveenhigh confidence
Why it matters
- →Dots establishes OpenAI's infrastructure for always-on agents with direct billing via Astra.
- →GPT-6.1 introduces optimized pricing for caching, reducing costs for high-frequency agent calls.
- →Codex in the cloud enables voice and computer use, expanding autonomous coding workflows.
OpenAI announced its latest suite of developer tools at DevDay, centering on autonomous agents and cloud-based coding environments. Key releases include Dots, an always-on personal agent powered by the Astra model, and GPT-6.1, which introduces new pricing structures for caching and agent usage. The company also launched Codex in the cloud, adding voice interaction and computer use capabilities to its code execution environment. Additionally, OpenAI expanded its ecosystem with a new Apps SDK, plugin extensions, and an integrated marketplace for distributing AI applications.
Read originalThe story around this
Earlier coverage that leads up to this article, and what followed. Lines connect each piece to the closest one after it, converging here.
More from Sam Witteveen
© Sam WitteveenCoding Toolsagents
Specialized Image Models for RPA Decision Making
RPA has long struggled with unstructured visual inputs like forms and screenshots, often relying on brittle rule-based systems. This video explores two open models, ImaJev-4B and Jev-Omni, designed specifically to handle these image-based decisions. By focusing on confidence scores and conditional logic, these tools aim to bridge the gap between simple automation and true cognitive processing in document workflows. The approach moves beyond generic vision-language models to offer targeted accuracy for enterprise tasks like form inspection.
Sam Witteveen
© Sam WitteveenMore in Models & Labs
Models & Labsother
llama.cpp b11380 adds ROCm 10 and Snapdragon support
This release quietly cements llama.cpp as the universal inference runtime by finally bringing first-class ROCm 10.0 support to both Linux and Windows. AMD GPU users no longer need workarounds, effectively closing a long-standing parity gap with NVIDIA's CUDA ecosystem. Equally notable is the new Snapdragon binary for Linux, which unlocks local AI on ARM-based laptops using Adreno GPUs and Hexagon NPUs. While KleidiAI on macOS has been disabled in this build, the expansion to AMD and Qualcomm hardware makes this a critical update for anyone running inference outside of the NVIDIA walled garden.
llama.cpp Releases
Models & Labsother
llama.cpp b11382 adds ROCm 10 and Snapdragon support
This release quietly cements llama.cpp as the universal inference runtime by finally bringing first-class ROCm 10.0 support to both Linux and Windows. AMD GPU users no longer need workarounds, effectively closing a long-standing parity gap with NVIDIA's CUDA ecosystem. Equally notable is the new Snapdragon binary for Linux, which unlocks local AI on ARM-based laptops using Adreno GPUs and Hexagon NPUs. While KleidiAI on Apple Silicon has been disabled in this build, the expansion to AMD and Qualcomm hardware makes llama.cpp significantly more accessible for diverse consumer hardware.
