🧩 DeepSeek Harness v0.1 is now available in Developer Preview!
🔹 We’re opening it up to developers building agent harnesses worldwide and open-sourcing the codebase in MIT license.
🔹 Powered by the Cordis meta-framework, DeepSeek Harness is an agent harness built around one core idea: Everything is a plugin. Models, tools, skills, sessions, sandboxes, filesystems, loops, orchestration, and UI are ALL implemented as plugins, and can be mixed, matched, replaced, and extended.
Try it now!
https://t.co/2YWSvJHhKA
We made the first 110-minute AI feature film with a real cast, The Cully Hill Boys, on Higgsfield for $2,000,000.
Starring @N3onOnYT, @stylebender, @RampageJackson, and @MKIATPIS
It's 100% open-sourced on Higgsfield: all prompts and assets are public now.
Made with Seedance on Higgsfield.
Watch full film below 👇
🎨 Meet Qwen-Image-3.0 — the third generation of our foundational image generation model.
If 1.0 was about "Precision," and 2.0 added "Variety, Completeness, Beauty & Authenticity," then 3.0 comes down to a single word: Real (实).
Three dimensions of "Real":
📰 Rich Content — prompts up to 4.5k tokens. One-pass generation of complex layouts: newspapers, storyboards, exam papers — even a 3×3 infographic grid or picture-in-picture-in-picture UIs.
🔬 Authentic Details — text legible down to 10px, full LaTeX paper pages, pores, hair strands & near-photographic skin texture.
🌏 Deep Knowledge — native rendering in 12 languages, 100+ art styles, realistic UIs (web / games / livestreams), plus world knowledge & live web retrieval.
Not just "good-looking" — genuinely useful. Image generation as a real productivity tool for design, content, education & e-commerce.
Go create 🏃🎨
💬Qwen Chat: https://t.co/941HmITJ2W
📝Blog: https://t.co/5mnS4uI9Ar
Introducing FLUX 3.
One multi-modal model for Image, Video, Audio and Action-Prediction. Creations are truer to life in every kind of style.
FLUX 3 Video is now available in early access (link below).
Jointly trained in one unified architecture, our model can be extended to predict actions for robotics. See our work with mimic and Audi in the thread.
INSID3 segments objects across domains using ONLY ONE annotated example
it works entirely without a segmentation decoder, task-specific fine-tuning, or external mask generators like SAM
CVPR 2026 paper with enormous practical potential