image-generation

Image model releases are generating 6.5 times more mobile app downloads than traditional text model updates, according to Appfigures. Google's Gemini added 22 million downloads in 28 days following its image model release, while ChatGPT added 12 million after GPT-4o image capabilities launched.

OpenAI's ChatGPT Images 2.0 has added UI design analysis capabilities, allowing it to review interface designs, flag specific issues, and generate redesigned mockups. The feature is available to ChatGPT Plus subscribers at $20/month and represents an expansion beyond pure image generation into design review.

OpenAI's ChatGPT Images 2.0 scored 97% versus Google's Gemini Nano Banana at 85% in a nine-test image generation benchmark conducted by ZDNET. The tests measured capabilities including image restoration, text rendering, and prompt adherence, with Nano Banana losing points primarily for fabricating details and text errors.

OpenAI released ChatGPT Images 2.0, pricing output tokens at $30 per million with maximum resolution of 3840x2160 pixels. CEO Sam Altman claims the improvement from gpt-image-1 to gpt-image-2 equals the jump from GPT-3 to GPT-5.

OpenAI has released ChatGPT Images 2, an upgraded image generation model that produces images up to 2K resolution in multiple aspect ratios. The model ships with two versions—Instant and Thinking—and can research current web information before generating images.

OpenAI is set to announce gpt-image-2, its next-generation image generation model, on April 21, 2026 at 12pm PT. The company's teaser demonstrates improved capabilities in rendering text and generating realistic user interfaces from text prompts.

Google has integrated its Nano Banana image generation system with Gemini's Personal Intelligence feature, enabling the AI to create images informed by user data from Gmail, Photos, Calendar, Drive, and other Google apps. The feature rolls out to Plus, Pro, and Ultra subscribers in the US first, with Europe excluded from the initial launch.

Google's Gemini can now generate personalized images by pulling data from users' Google Photos libraries through its Personal Intelligence feature. The integration uses Google Photos labels to identify people and objects, then generates images via the Nano Banana 2 model that reflect users' tastes and lifestyle.

Baidu has released ERNIE-Image-Turbo, a distilled text-to-image diffusion transformer that generates images in 8 inference steps. The model runs on consumer GPUs with 24GB VRAM and supports resolutions up to 1376×768, with claimed strengths in text rendering and structured generation tasks.

Stability AI has launched Brand Studio, a commercial platform designed for creative teams to generate AI images aligned with their brand identity. The platform includes Brand Central for training custom models, Producer Mode for automated visual workflows, and Curated Model Routing that selects optimal models for specific tasks.

Stability AI and NVIDIA have launched Stable Diffusion 3.5 NIM, a microservice designed to accelerate image generation performance and simplify enterprise deployment. The collaboration packages Stable Diffusion 3.5 as an NVIDIA NIM (NVIDIA Inference Microservice) for optimized inference.

Stability AI has released TensorRT-optimized versions of the Stable Diffusion 3.5 model family in collaboration with NVIDIA. The optimization uses FP8 quantization to achieve 2x faster generation speed and 40% lower VRAM requirements on supported RTX GPUs.

Stability AI has released ONNX-optimized versions of Stable Diffusion engineered to run faster and more efficiently on AMD Radeon GPUs and Ryzen AI APUs. The collaboration with AMD targets broader hardware compatibility for the image generation model.

Stability AI's Stable Diffusion 3.5 Large model is now available through Microsoft Azure AI Foundry, giving businesses integrated access to professional-grade image generation within Azure's ecosystem. The deployment expands SD3.5 Large's availability across major cloud platforms.

Adobe is rolling out custom models for Firefly, allowing creators to train the generative model on 10-30 of their own images to generate new content matching their specific visual style. The feature costs 500 credits per training session and supports three methods: photography style, illustration style, and character consistency.

Microsoft's superintelligence team, led by Mustafa Suleyman, has released MAI-Image-2, a text-to-image generator that currently ranks third on the Arena.ai leaderboard for text-to-image models, behind OpenAI's GPT-Image-1.5 and Google's Nano Banana 2. The model is now available for testing in the MAI Playground and will roll out to Copilot and Bing Image Creator, with API access opening to all developers through Microsoft Foundry.

Midjourney has released an early version of V8 for community testing, achieving roughly 5x faster image generation and introducing native 2K resolution via --hd mode. However, premium features including --hd, --q 4, style references, and mood boards cost four times as much as standard generation, with Relax mode unavailable at launch.

Google DeepMind has released Nano Banana 2, an image generation model that combines advanced world knowledge and subject consistency with faster inference speeds comparable to its Flash offering. The model is positioned as production-ready with capabilities previously associated with Pro-tier performance.

Google has relaunched its Flow AI creative studio as a unified platform for image and video creation. The updated tool includes free image generation capabilities and new editing features designed to streamline creative workflows.

Segmind has released SegMoE, a mixture-of-experts (MoE) diffusion model designed to accelerate image generation while reducing computational overhead. The model applies MoE techniques traditionally used in large language models to the diffusion model architecture, enabling selective expert activation during inference.