text-to-image

Google has released Gemini 3.1 Flash Lite Image, also called Nano Banana 2 Lite, which the company describes as its fastest and cheapest image generation model. The model is available through Google's AI Studio and Gemini API with the identifier gemini-3.1-flash-lite-image.

Google has released Gemini 3.1 Flash Lite Image, a text-to-image model that generates 1K resolution images in approximately 4 seconds — 2.7× faster than Gemini 3.1 Flash Image. The model is priced at $0.25 per 1M input tokens and $1.50 per 1M output tokens, with a 66K context window and knowledge cutoff of January 2025.

Krea.ai released Krea 2 Turbo, a 12-billion parameter diffusion transformer model for text-to-image generation. The open-weight model generates images in 8 inference steps and supports resolutions up to 2048x2048 pixels.

Ideogram has released Ideogram 4, its first open-weight text-to-image model with 9.3 billion parameters. The model supports native 2K resolution, structured JSON prompting with bounding-box layout controls, and is available in nf4 and fp8 quantizations under a non-commercial license.

Ideogram has released Ideogram 4, a 9.3B parameter open-weight text-to-image model trained from scratch. The model features structured JSON prompting, native 2K resolution output, and ranks as the top open-weight model on Design Arena. Available in fp8 and nf4 quantizations under a non-commercial license.

NVIDIA released Cosmos3-Super-Text2Image, a 64-billion parameter text-to-image generation model as part of its Cosmos3 collection of omnimodal world models. The model uses a Mixture-of-Transformers architecture combining autoregressive and diffusion transformers, designed for Physical AI applications including robotics and autonomous vehicles.

Microsoft released Lens, a 3.8-parameter foundational text-to-image model trained on Lens-800M, an 800 million image-text corpus with GPT-4.1 captions. The model uses a 48-block MMDiT denoiser with FLUX.2 latents and supports generation up to 1440×1440 resolution across aspect ratios from 1:2 to 2:1.

ByteDance has released Lance, a 3-billion parameter multimodal model that performs image and video generation, editing, and understanding within a single framework. The model was trained entirely from scratch using 128 A100 GPUs and achieves 84.67% on DPG-Bench and 74% on GenEval, competing with larger models despite its compact size.

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.

Baidu has released ERNIE-Image, an 8B parameter text-to-image generation model built on a single-stream Diffusion Transformer architecture. The model is designed for complex instruction following, text rendering, and structured image generation, and can run on consumer GPUs with 24GB VRAM.

Microsoft released public preview versions of three proprietary AI models: MAI-Transcribe-1 for speech recognition across 25 languages at 50% lower GPU cost than alternatives, MAI-Voice-1 for speech synthesis generating 60 seconds of audio in under a second, and MAI-Image-2 for text-to-image generation. The models are available exclusively through Microsoft Azure AI Foundry and already power Copilot, Bing, and PowerPoint.

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.