Artificial Analysis reports that Grok Imagine Video 1.5 Lite comes closest to the frontier in Architecture & Real Estate, Consumer, and Productivity & Knowledge Work use cases. It sits furthest from the frontier in Live-Action Film and Frontier use cases. Against Grok Imagine Video 1.5, Lite matches it in Social Media & Creator Content and trails it on the other nine use cases.
Grok Imagine Video 1.5 Lite sits on the quality and speed frontier on AA-Video-T2V-Silent v2.0 Among the 12 models on AA-Video-T2V-Silent v2.0 that we benchmark for generation speed, no model is both faster and higher quality than Grok Imagine Video 1.5 Lite. It generates a 10 second 1080p clip in a median of 60.5 seconds. Kling 3.0 1080p (Pro) scores slightly higher and takes 94 seconds for a 5 second clip. Vidu Q3 Turbo is 9 seconds faster on a 5 second 720p clip, and scores well below it.
> A completely filled up glass of wine and a clock at 3:30pm - Nano Banana 2.1
Mask-based editing is my favorite from today, much more coming soon!
🐶 Successful pug smiles, courtesy of @nanobanana 2.1. Try it out in @googleaistudio today!
introducing @NanoBanana 2.1 🍌 our latest image generation model outperforms our previous models across the board: - better visual design - mask-based editing - subject consistency - more natural-looking images try it out today in https://ai.studio
Google has released Nano Banana 2.1, an image generation and editing model on its Flash tier that succeeds Nano Banana 2 and Nano Banana Pro. The source says it improves product recontextualization, though the excerpt provides no further details on benchmarks, pricing, or availability.
New imagination. New stories. New ways to create. ✨ See what creators are making with Kling 4.0 and Kling 4.0 Flash.
Google has made Gemini Nano Banana 2.1, identified as gemini-nano-banana-2.1, generally available as an image generation and conversational editing model. It improves visual quality, prompt adherence, multi-turn character consistency, and text rendering, and adds panoramic aspect ratios such as 1:4, 4:1, 1:8, and 8:1 at 1K, 2K, and 4K resolutions. The gemini-3.1-flash-image model is deprecated with no shutdown date announced, and developers are told to migrate to the new model.
LiquidAI has released d1-omni-600M on Hugging Face, a 587M-parameter model that answers named yes/no, choice and score questions over text, images or up to 30 seconds of speech in a single forward pass. It returns typed answers with zero output tokens by reading the model's distribution over options, and is built on LFM2.5-Encoder-350M with a 16,384-token context length. The model is not a chat model and does not generate text.
NVIDIA has released PixelUMM, an encoder-free unified multimodal model with 15,199,672,064 parameters that handles text, image, and video understanding and generation directly in pixel space. It represents images as 16-by-16 RGB pixel patches on a Qwen3-8B language backbone, with iterative denoising for generation. The checkpoint is licensed for non-commercial research or evaluation only, while the source code is under Apache License 2.0.
FLUX 3 Image is here. The latest from @bfl_ai, generate stunning native 4K imagery, and get maximum control over every pixel. Construct images with hyper-specific layouts using bounding boxes, make multiple targeted edits at once, and stay consistent across edits. For its first week, it's 50% off.
Alibaba's Wan 3.0 ranks #1 overall on the new Artificial Analysis AA-Video-T2V v2.0 text-to-video leaderboard, priced at $12 per minute of video. The benchmark judges models at 1080p using over 68,000 human preference votes across 1,000 prompts, and the author states Wan 3.0 leads 10 of 20 category boards.
While ideogram 4.5 was specifically built for precise and targeted editing, it performs extremely well across general editing tasks.
Ideogram has launched Ideogram 4.5, an image editing model that is now live in Ideogram, the API, and launch partners. Open weights are coming soon. The launch post says the model avoids artifact buildup and pixel shifts across repeated edits, making multi-turn editing possible.
Ideogram 4.5 comes in four quality modes, ranging from 0.8¢ to 22¢ per image, all at native 2K resolution. Available now on our launch partners: @superscale_ai @Picsart @cfabricacom @luminal_ai @arena @runware @florafaunaai @krea_ai @trymoda @LeonardoAi @runwayml @pika_labs @fal @ComfyUI @magnific @GammaApp @LumaLabsAI @DesignArena
Here's a side-by-side comparison of the same edits on Ideogram 4.5 vs. GPT Image 2.5 Sunburst, Nano Banana Pro, and Nano Banana 2. GPT Image and Nano Banana outputs become unusable within a few edits, while Ideogram 4.5 stays clean edit after edit.
Introducing Ideogram 4.5, the most precise edit model. With each edit, leading models add artifacts, pixel shifts, and color changes. Ideogram 4.5 eliminates artifact buildup, making multi-turn editing possible. Live in Ideogram, the API, and launch partners. Open weights soon.
ModelScope released Qwen-Image-2.1-Fun-Controlnet-Union, a single checkpoint adding eight structural controls, including Canny, Depth, Pose, and Scribble, plus inpainting to Qwen-Image 2.1. Control and inpainting share one branch with 16 injection points across every second Transformer block, keeping the base model frozen and requiring no checkpoint switching. It runs at guidance scale 1.0 with CFG-distilled sampling and prefix KV caching, and is available under the Qwen Research License with base Qwen-Image 2.1 weights required.
No lab has reached the image frontier faster. Microsoft AI: 864 → 1147 Elo in nine months. That's 377 points a year — 1.6× the next-fastest climb on the board.
Tencent has released a preview of its Hy Image 3.5 image generation model, which product teams across Yuanbao, WorkRally, Ima, and other services are helping refine through co-design. Tencent Cloud prices the model at USD 0.024 per 2K output image, and it supports text-to-image and image-to-image generation with up to five reference images. Tencent said an internal blind evaluation found it on par with ByteDance's Seedream 5.0 Pro and slightly better than Nano-Banana Pro and Qwen-Image-3.0 Pro.
inclusionAI open-sources the Ming-Image-0.1-Design family, two complementary 6B models for visual-design workflows, under an MIT License. Design generates complete UIs, dashboards, infographics, and posters up to 2048×2048 with native transparent RGBA output, and Layer decomposes flattened graphics into independently editable RGBA layers.
Thanks @arena for the recognition! 🏆 Qwen-Image-2.1 is now the #1 open-source model in both the Image Edit and Text-to-Image Arenas. Try it now and show us what you create! 🎨
Sure you can edits images with this model.✔️
Qwen-Image-2.1 also improves visual quality over its predecessor, particularly in the aesthetics of text and portraits. Below are several examples of text rendering.
Qwen-Image-2.1 supports a variety of editing tasks while balancing performance across them. For example, given a three-view character reference, the model generates a complete storyboard.
Qwen-Image-2.1 supports up to 10 reference images and can produce high-quality results.
Qwen-Image-2.1 now supports transparent image generation natively, and naturally supports editing transparent images as well.
Alibaba's Qwen team released Qwen-Image-2.1 as an open-weights image model for both generation and editing, with a lightweight 7B architecture. The model natively generates and edits RGBA layers, supports up to 10 reference images for editing, and is available on GitHub, ModelScope, and Hugging Face.
Alibaba's ModelScope introduces Qwen-Image-2.1, a model that handles image generation and editing together, with native transparency and a compact 7B visual generation component. It adds KV cache reuse to speed up generation and editing while reducing memory use, especially with multiple reference images. The model can combine up to 10 reference images, make targeted local edits, and preserve portrait identity and product details.
Qwen has open-sourced Qwen-Image-2.1, a unified text-to-image generation and image editing model with 7B visual generation parameters. The Hugging Face page for Qwen-Image-2.1-PE-I2I is a fine-tuned Qwen3.5-VL 9B prompt rewriter that turns vague editing instructions and input images into precise editing prompts, supporting up to 10 reference images.
AIWhy it matters: The model card documents usage with transformers and diffusers, letting readers see how the editing prompt rewriter connects to the generation pipeline.
Qwen has open-sourced Qwen-Image-2.1, a unified text-to-image generation and image editing model with a 7B-parameter visual generation component. The release also includes Qwen-Image-2.1-PE-T2I, a fine-tuned Qwen3.5-VL 9B model that rewrites brief image requests in any language into detailed English prompts with a recommended aspect ratio.
AIWhy it matters: The release pairs a 7B visual generation component with a separate prompt rewriting model, showing how a brief image request becomes a detailed English prompt before rendering.
inclusionAI has released Ming-Image-0.1-Design-Layer on Hugging Face, a model that decomposes a flattened design image into a requested number of RGBA layers using an image and a layer plan. The model runs at 1024 resolution (512 for faster processing) with 12 sampling steps, a CFG scale of 2.0, and BF16 precision on one CUDA GPU with 80 GiB VRAM. It is released under the MIT License.
inclusionAI has released Ming-Image-0.1-Design, a 6B text-to-image model for UI, infographics, and posters that outputs RGBA images with transparent backgrounds. The model is available on Hugging Face and ModelScope under the MIT License. It runs at 2048 x 2048 with 12 sampling steps and a CFG scale of 1.0, validated on one CUDA GPU with 80 GiB VRAM.
Don't forget that GPT Image 2.5 is now live in ChatGPT! It's incredible at keeping consistency while editing images, and SOTA on all image leaderboards. If you've been burned by faces slightly changing when editing with GPT Image 2, give it another try! https://openai.com/index/introducing-chatgpt-images-2-5/
Qwen has open-sourced Qwen-Image-2.1, a unified text-to-image generation and image editing model with 7B parameters in its visual generation component. The model can generate regular or transparent RGBA images, supports up to 10 reference images for editing, and is licensed under the Qwen Research License Agreement.
AIWhy it matters: The source specifies the 7B visual component, transparent RGBA output, and up to 10 reference images, which helps readers judge its fit for generation and editing workflows.
MAI-Image-2.6 and new MAI-Image-2.6-Flash are redefining the Artificial Analysis quality/price Pareto frontier for image editing. Both now in Microsoft Foundry: https://msft.it/6018aVgIQ
Our new image model generates images 2x faster than GPT-Image-2, currently the best model in the world. It's also 72% more efficient in GPU usage, so we can provide it at an incredible price. This gives it the best price-performance score in the world. Unbelievable work from the team. So much more to come! Try MAI-Image-2.6-Flash out now!
MAI-Image-2.6-Flash has the best price/quality in the world.
Lyria 3.5, our best-sounding music generation model, is now available in AI Studio, via the Gemini API, and in the Gemini app this model brings more expressive vocals and richer musical arrangements, allowing you to craft tracks with higher fidelity try it today: http://ai.studio