What shipped in AI.

Mage-VL-Cowork A Full Training Recipe to Learn Hybrid Computer Use from Evolved Harnesses

FrogNano is a compact 4B coding agent from Microsoft, trained with reinforcement learning on about 1,500 synthetic software engineering tasks. It generates structured tool calls for the Leaf harness to work on repository issues, and its patches still need human review.

Streaming ASR model that transcribes speech as it arrives and attributes each utterance to a speaker (who said what). Users can supply custom hotwords such as names and technical terms, and the card lists ten languages.

Mage-ViT is a vision encoder that uses codec signals to keep only motion-salient patches, which makes video processing efficient. This repo ships only the ViT checkpoint without language model training and can serve as an encoder for your own multimodal training.

Mage-VL is a 4B multimodal model for image and video understanding. It pairs a visual encoder trained from scratch with a Qwen3-4B language backbone. The modelcard reports over 75% fewer visual tokens and up to 3.5x faster inference than uniform frame sampling.

Compressed speech recognition model derived from VibeVoice-ASR for real-time transcription on CPUs without a GPU. The model card reports RTF below 1 from 3 threads at a total size of 1.58 GB.

Microsoft's specialized code-search model for coding agents — powers the 'Explore' subagent in SWE-FastContext. Not a general-purpose LLM, but relevant for agentic setups.