Exciting news from Jasper Research! 🚀 We built an... internal 4B text-to-image model from scratch that turned out to be one of the fastest models out there! 1k image generation in less than a second! Our technical report shares everything we learned along the way. 👇show more

Exciting milestones in our generative AI research: Emu Video,... which lets you create high quality videos from a text prompt, and Emu Edit, which enables detailed image editing based on your instructions. These new models are built on Emu, our foundation model for image generation and technology from them will underpin new creative features across our apps next year. Try it out: Emu Video: Emu Edit:show more

TurboEdit Instant text-based image editing discuss: We address the... challenges of precise image inversion and disentangled image editing in the context of few-step diffusion models. We introduce an encoder based iterative inversion technique. The inversion network is conditioned on the input image and the reconstructed image from the previous step, allowing for correction of the next reconstruction towards the input image. We demonstrate that disentangled controls can be easily achieved in the few-step diffusion model by conditioning on an (automatically generated) detailed text prompt. To manipulate the inverted image, we freeze the noise maps and modify one attribute in the text prompt (either manually or via instruction based editing driven by an LLM), resulting in the generation of a new image similar to the input image with only one attribute changed. It can further control the editing strength and accept instructive text prompt. Our approach facilitates realistic text-guided image edits in real-time, requiring only 8 number of functional evaluations (NFEs) in inversion (one-time cost) and 4 NFEs per edit. Our method is not only fast, but also significantly outperforms state-of-the-art multi-step diffusion editing techniques.show more

LLM-grounded Diffusion: Enhancing Prompt Understanding of Text-to-Image Diffusion Models... with Large Language Models paper page: github: Recent advancements in text-to-image generation with diffusion models have yielded remarkable results synthesizing highly realistic and diverse images. However, these models still encounter difficulties when generating images from prompts that demand spatial or common sense reasoning. We propose to equip diffusion models with enhanced reasoning capabilities by using off-the-shelf pretrained large language models (LLMs) in a novel two-stage generation process. First, we adapt an LLM to be a text-guided layout generator through in-context learning. When provided with an image prompt, an LLM outputs a scene layout in the form of bounding boxes along with corresponding individual descriptions. Second, we steer a diffusion model with a novel controller to generate images conditioned on the layout. Both stages utilize frozen pretrained models without any LLM or diffusion model parameter optimization. We validate the superiority of our design by demonstrating its ability to outperform the base diffusion model in accurately generating images according to prompts that necessitate both language and spatial reasoning. Additionally, our method naturally allows dialog-based scene specification and is able to handle prompts in a language that is not well-supported by the underlying diffusion model.show more

CosmicMan A Text-to-Image Foundation Model for Humans We present... CosmicMan, a text-to-image foundation model specialized for generating high-fidelity human images. Unlike current general-purpose foundation models that are stuck in the dilemma of inferior quality andshow more

Introducing SDXL Turbo: A real-time text-to-image generation model. SDXL... Turbo achieves state-of-the-art performance with a new distillation technology, enabling single-step image generation with unprecedented quality, reducing the required step count from 50 to just one. The code, research paper, and weights for non-commercial use are now available on our website. You can test SDXL Turbo on Stability AI’s image editing platform Clipdrop, with a beta demonstration of the real-time text-to-image generation capabilities. Learn more:show more

We’re excited to announce the release and open-source of... HunyuanImage 3.0 — the largest and most powerful open-source text-to-image model to date, with over 80 billion total parameters, of which 13 billion are activated per token during inference.The effect is completely comparable to the industry’s flagship closed-source model.🚀🚀🚀 HunyuanImage 3.0 originates from our internally developed native multimodal large language model, with fine-tuning and post-training focused on text-to-image generation. This unique foundation gives the model a powerful set of capabilities: ✅Reason with world knowledge ✅Understand complex, thousand-word prompts ✅Generate precise text within images Different from traditional DiT architecture image generation models, HunyuanImage 3.0’s MoE architecture uses a Transfusion-based approach to deeply couple Diffusion and LLM training for a single, powerful system. Built on Hunyuan-A13B, HunyuanImage 3.0 was trained on a massive dataset: 5 billion image-text pairs, video frames, interleaved image-text data, and 6 trillion tokens of text corpora. This hybrid training across multimodal generation, understanding, and LLM capabilities allows the model to seamlessly integrate multiple tasks. Whether you're an illustrator, designer, or creator, this is built to slash your workflow from hours to minutes. HunyuanImage 3.0 can generate intricate text, detailed comics, expressive emojis, and lively, engaging illustrations for educational content. The current release focuses solely on text-to-image generation and future updates will include image-to-image, image editing, multi-turn interaction, and more. 👉🏻Try it now: 🔗GitHub: 🤗Hugging Face:show more

T2I-CompBench: A Comprehensive Benchmark for Open-world Compositional Text-to-image Generation... paper page: Despite the stunning ability to generate high-quality images by recent text-to-image models, current approaches often struggle to effectively compose objects with different attributes and relationships into a complex and coherent scene. We propose T2I-CompBench, a comprehensive benchmark for open-world compositional text-to-image generation, consisting of 6,000 compositional text prompts from 3 categories (attribute binding, object relationships, and complex compositions) and 6 sub-categories (color binding, shape binding, texture binding, spatial relationships, non-spatial relationships, and complex compositions). We further propose several evaluation metrics specifically designed to evaluate compositional text-to-image generation. We introduce a new approach, Generative mOdel fine-tuning with Reward-driven Sample selection (GORS), to boost the compositional text-to-image generation abilities of pretrained text-to-image models. Extensive experiments and evaluations are conducted to benchmark previous methods on T2I-CompBench, and to validate the effectiveness of our proposed evaluation metrics and GORS approach.show more

New from Meta FAIR: Code World Model (CWM), a... 32B-parameter research model designed to explore how world models can transform code generation and reasoning about code. We believe in advancing research in world modeling and are sharing CWM under a research license to help empower the community to build upon our work. ➡️ Read the technical report: ➡️Download the open weights: ➡️Download the code:show more

We've officially released and open-sourced HunyuanImage 2.1, our latest... text-to-image model. The new model delivers on our commitment to balancing performance and quality. With native 2K image generation, HunyuanImage 2.1 is an advanced open-source text-to-image model.🎨 ✨ New in 2.1: 🔹Advanced Semantics: Supports ultra-long and complex prompts of up to 1000 tokens, and precisely controls the generation of multiple subjects in a single image. 🔹Precise Chinese and English Text Rendering with seamless image–text integration: The model naturally integrates text into images, making it suitable for a wide range of applications such as product covers, illustrations, and poster design to meet the needs of various fields. 🔹Rich Styles and High Aesthetic: Capable of generating images in various styles—including photorealistic portraits, comics, and vinyl figures—it delivers outstanding visual appeal and artistic quality. 🔹High-Quality Generation: Efficiently produces ultra-high-definition (2K) images in the same time other models take to generate a 1K image. HunyuanImage 2.1 uses two text encoders: a multimodal large language model (MLLM) to improve the model's image and text alignment capabilities, and a multi-language character-aware encoder to improve text rendering capabilities. The model is a single- and double-stream diffusion transformer with 17B parameters. We've also open-sourced the weights of the the accelerated version with meanflow which reduces inference steps from 100 to just 8, and PromptEnhancer, the first industrial-grade rewriting model that enhances your prompts for more nuanced and expressive image generation. Now, creators turn complex ideas—like posters with slogans or multi-panel comics—into visuals faster than ever. We’re just getting started. Stay tuned for our native multimodal image generation model coming soon. 🌐Website: 🔗Github: 🤗Hugging Face: ✨Hugging Face Demo:show more

🔒 Exciting news! The long-awaited 𝐬𝐭𝐚𝐤𝐢𝐧𝐠 𝐩𝐥𝐚𝐭𝐟𝐨𝐫𝐦 is finally... on its way! ✅ Built and coded from scratch, check! ✅ Internal testnet, check! 🔍 Audit, currently in progress! 🚀 Soon to be released for selected testers! The next Galxe campaign? On its way!show more

Qwen‑Image‑2.0 continues to push what’s possible in next‑gen image... generation. From pro typography rendering and stronger semantic adherence to improved text rendering and a lighter model, it keeps delivering creative power with ease. Check out the demos to discover more!show more

You imagine it. We create it. 🎨 Introducing #PixelStudio,... a first-of-its-kind image generator on #Pixel9 powered by an on-device diffusion model¹ running on Tensor G4 and our Imagen 3 text-to-image model in the cloud.show more

Generate persistent 3D worlds from a single image, bigger... and better than ever! We’re excited to share our latest results and invite you to try out our world generation model in a limited beta preview.show more

1/4 🚀We are launching Qwen-Image-2.0, a next-generation foundational image... generation model. The key highlights of Qwen-Image-2.0 include: Professional Typography Rendering: Supports 1k-token instructions for direct generation of professional infographics, including PPTs, posters, comics, and more. Stronger Semantic Adherence: Native 2K resolution support for finely detailed realistic scenes, including people, nature, and architecture. Improved Text Rendering: Integrated understanding and generation capabilities, unifying image generation and editing in a single mode Lighter Model Architecture: Smaller model size with faster inference speed.show more

Qwen‑Image‑2.0 continues to push what’s possible in next‑gen image... generation. From pro typography rendering and stronger semantic adherence to improved text rendering and a lighter model architecture, it keeps delivering creative power with ease ✨ Check out the demos to discover more!show more

We have updated some of our NFTs to allow... them to load as 3D models in your pods 🪴🚀. Post an image or a link to your customized pod! 👇show more

most AI APIs either cost too much or lock... the best models behind expensive plans. then i came across Agnes AI. it’s one of the few platforms giving developers access to text, image, and video AI models through a single API. their ecosystem gives you direct access to top-tier models like - Agnes-2.0-Flash for text - Agnes-Image-2.0 for image - Agnes-Video-V2.0 for video Instead of managing different providers for different tasks, everything works from one place. what stood out to me: > one API for text, image, and video generation > OpenAI-compatible API, so integration is straightforward > built for speed and scalability > free access for developers to start building > useful for everything from chatbots to image generation and content automation if you’re building AI products, it’s worth taking a look while it’s still flying under the radar. sometimes the biggest advantage is finding great tools before everyone else does. check out Agnes AI here, get free access for developers : and if you’re building with it, join the developer community here: Agnes AI #AgnesAI #AgnesAPI #BuildWithAgnes #MultimodalAI #AIforDevs #DeveloperAPI #AIParityshow more

Grok now brings images to life. I don’t know... about you, but sounds an awful lot like Revelation 13:15- “The second beast was given power to give breath to the image of the first beast, so that the image could speak and cause all who refused to worship the image to be killed.” We are watching biblical prophecy come to life, and this administration is setting everything up right in front of our eyes. What an honor it is to be the generation!show more