What shipped in AI.

Ming-Image-0.1-Design is a 6B text-to-image model for UI, infographics, posters, and other text-rich visual designs. It generates complete visual compositions and supports RGBA output with transparent backgrounds.

Ming-Image-0.1-Design-Layer decomposes a flattened design image into a requested number of RGBA layers using an image and a layer plan.

A full-duplex interaction system with asynchronous delegation

LLaDA-UI is an MoE-based, block-wise diffusion vision-language GUI agent. It understands screenshots at their native aspect ratio and produces grounded coordinates or structured actions for mobile, desktop, and web interfaces.

LLaDA2.2-mini is the lightweight variant of the agentic diffusion language model in the LLaDA2 series.

Ling 3.0 Flash VL builds on Ling 3.0 Flash (124B total / 5.5B active MoE from InclusionAI), further strengthening its language capabilities while adding native visual perception and advanced visual...

Ling 3.0 Flash Sante is a health and medicine-focused mixture-of-experts model from InclusionAI, built on Ling 3.0 Flash with 5.1B active parameters out of 124B total. It is designed for...

LLaDA-Image: Building Strong Image Generators with Fully Open Training Recipes

Ling 3.0 Flash Fin is a finance-focused mixture-of-experts model from InclusionAI, built on Ling 3.0 Flash with 5.1B active parameters out of 124B total. It is designed for real-world investment...

Ling-3.0-tiny is a 7.9B hybrid MoE language model that activates only 1.3B parameters per token. It combines a 3:1 alternating layout of Kimi Delta Attention and Multi-Head Latent Attention layers with a sparse MoE feed-forward network of 128 experts (8 routed plus 1 shared per token). The model provides reasoning via a configurable thinking mode, supports multi-turn tool calling through XML-tagged function calls, and offers BF16, FP8, and INT4 quantized weights. Benchmarks report around 160+ tokens/s inference speed on an H20 GPU, approximately 8.3 GiB peak VRAM at 8K context in FP8, and an Artificial Analysis Intelligence Index score of 25 and Agentic Index score of 16. SGLang integration includes a built-in speculative decoding recipe (NEXTN/MTP) and YaRoN-based context extension up to 262K tokens. No explicit evaluation table values are published in the released material beyond those two index scores.

Ling-3.0-flash is a 124B-parameter Mixture-of-Experts (MoE) model, with approximately 5.1B parameters activated per token. The model is designed with token efficiency and production-scale agentic inference as key priorities, enabling developers...

LLaDA2.2-flash is an agent-oriented diffusion language model in the LLaDA2 series.

VISTA-9B are GUI-grounding vision-language models trained from Qwen3.5 9B backbones with VISTA: View-Consistent Self-Verified Training for GUI Grounding.

Ant Group's (Alipay's parent) 1-trillion-parameter MoE model — Apache 2.0. Extremely cheap on OpenRouter ($0.075/$0.625 per MTok). 472 likes on HF despite barely any Western coverage.