AI & Software

Qwen-Image-2.1 Hugging Face: https://huggingface.co/Qwen/Qwen-Image-2.1, https://huggingface.co/Qwen/Qwen-Image-2.1-Turbo GitHub: https://github.com/QwenLM/Qwen-Image-2.1 Website: https://qwen.ai/blog?id=qwen-image-2.1 Developer: Alibaba Cloud, Qwen team Released: September 2026 Variants: Qwen-Image-2.1 (40 default denoising steps) / Qwen-Image-2.1-Turbo (8 denoising steps) Parameters: 7B visual generation component, plus Qwen3-VL 8B text encoder Resolution: native 2K, 2048x2048 default; recommended sizes include 2752x1536 and 1536x2752 Architecture: single-stream DiT, 32 layers, block-causal attention with prefix KV cache reuse; Qwen3-VL 8B text encoder; 64-channel RGBA VAE with 16x spatial compression; flow matching with Euler scheduler License: Qwen Research License Agreement Modalities: Text-to-Image + Image editing (up to 10 reference images), native RGBA transparency Runs on: Desktop GPU, 24GB+ VRAM with model CPU offload Formats: BF16 safetensors, Diffusers pipeline On disk: Qwen-Image-2.1: 33.13GB (14.23GB transformer, 17.53GB text encoder, 1.35GB VAE) / Turbo: 32.49GB (14.23GB transformer, 17.53GB text encoder, 0.68GB VAE)

Metacognition NavGPT3 Hugging Face: https://huggingface.co/Metacognition-AI/NavGPT3-8B, https://huggingface.co/Metacognition-AI/NavGPT3-4B GitHub: https://github.com/metacognitionai/NavGPT-3 Website: https://metacognitionai.github.io/NavGPT3/ Technical report: https://arxiv.org/abs/2610.10787 Developer: Metacognition Released: October 2026 Variants: 4B, 8B Parameters: 4.44B (4B checkpoint), 8.77B (8B checkpoint) Architecture: Qwen3-VL fine-tune with a two-layer MLP action head on the last prompt token’s hidden state; one 3,072-token visual budget shared across a four-view, up to 16-step image history License: GNU Affero General Public License v3.0 Modalities: Text + Four-view RGB image history in / 8 waypoints (x, y, theta) out Runs on: NVIDIA GPU (Linux) Formats: safetensors On disk: 9.66GB (4B checkpoint), 17.54GB (8B checkpoint)

JeongsLee MOTION GitHub: https://github.com/JeongsLee/MOTION Docs: https://github.com/JeongsLee/MOTION/blob/main/WEIGHTS.md Developer: Jeongsu Lee, Kyung Hee University Released: August 2026 Variants: MOTION, MOTION-S, 6-family joint-benchmark model, Poseidon-corpus IVP pretrain, six few-shot fine-tuned arms Parameters: MOTION: 156.9M / MOTION-S: 20.7M / joint-benchmark: 114M / IVP pretrain and fine-tuned: 161.9M Architecture: Per-step tendency as a gated sum of explicit physical-mechanism heads (transport, diffusion, pressure and density coupling, reaction, wave, curvature) plus an ungated state head; mechanism knockout and physical-equivalence tests; TensorFlow License: Code: MIT / weights: CC-BY-4.0 Modalities: 2D and 3D PDE fields in, 2D and 3D PDE fields out; nineteen equation families across nine governing systems Runs on: Inference from a released checkpoint: 1 GPU with 24GB or more, Linux Formats: TensorFlow 2.15 named-array .npz in tar archives On disk: MOTION: 580MB / MOTION-S: 152MB / joint-benchmark: 456MB / IVP pretrain: 648MB / IVP fine-tuned: 3.89GB tar

Raven from Moritz Rietschel, Philipp Hölzenbein, and Maximilian Rietschel An agent inside Rhino 8 that turns a text prompt or a reference image into native, editable Grasshopper definitions. Website: https://raven.build/ X: https://x.com/ravencad Instagram: https://www.instagram.com/ravencad/ YouTube: https://www.youtube.com/@RavenCAD Discord: https://discord.com/invite/nXbkvwXwBh Formats: 3DM, STEP, IGES, DWG, DXF, OBJ, STL, 3MF, SVG, PDF Kernel: openNURBS (Grasshopper definitions based) Moritz, Philipp, and Maximilian are the co-founders of Raven.

vcad Type: b-Rep based Website: https://vcad.io GitHub: https://github.com/ecto/vcad Created: 2026 License: Apache 2.0 Language: Rust Formats: STEP, STL, GLB, DXF Bindings: WASM

Bonsai 1 Bit Announcement: https://prismml.com/news/bonsai-8b Hugging Face: https://huggingface.co/prism-ml/Bonsai-8B-mlx-1bit Bonsai 1 Bit is a 1 bit language model that comes in 8B, 4B, and 1.7B parameter sizes. The 8B model is 1/16 the size of comparable 16 bit 8B open models with similar performance. At 1.15gb, this model can fit on many kinds of devices with 4-5x better energy efficiency