Best open image generation models

For image generation, license and sampling steps decide more than raw quality. Several top open models are free to try but restrict commercial use, and the number of denoising steps sets how many images a GPU makes per hour.

What matters for this task

Sampling steps. A diffusion model removes noise over many steps. Base models often use 30 to 50; distilled "turbo" or "schnell" variants cut this to a handful, which multiplies throughput. The card states the step count (or NFEs, number of function evaluations) the model was designed for.

Parameter count. Image models run from under 1B to over 20B parameters in the catalog. Larger models usually follow prompts better but need more memory per image. See VRAM and quantization for ways to shrink them.

Text in images. Rendering legible words (signs, posters, UI) separates models sharply. Check whether the card claims bilingual or multilingual text rendering.

Resolution. Models are trained at a native resolution; going far beyond it degrades results.

Editing. Some releases handle editing from reference images as well as generation.

License. Check commercial terms before building a product. This is the most common reason to rule a model out.

Picks by situation

Fast and openly licensed. Z-Image-Turbo (Tongyi-MAI, Apache 2.0) is a distilled 6B model that the card says needs only 8 NFEs, with accurate English and Chinese text rendering and sub-second latency on H800-class GPUs.

Fewest steps, Apache 2.0. FLUX.1 schnell (Black Forest Labs, about 11.9B parameters in the catalog) is licensed Apache 2.0 per the Hugging Face metadata and the FLUX repository. The Black Forest Labs repository lists it as a text-to-image model.

Highest quality from the FLUX line, non-commercial. FLUX.1 dev (about 11.9B parameters) uses the FLUX.1-dev Non-Commercial License per the Black Forest Labs repository, which also points to a separate paid license for commercial use. Good for research and evaluation, not for a product without that license.

Generation plus editing in one model. Qwen-Image-2.1 (Qwen) is described as a unified text-to-image and editing model with a 7B-parameter visual generation component. Its card sets 40 inference steps in the example code, and the license is the Qwen Research License, so check terms for commercial use.

Mature ecosystem and small size. Stable Diffusion XL base 1.0 (Stability AI, about 2.57B parameters in the catalog) is licensed CreativeML Open RAIL++-M and has the largest set of community add-ons. It is a two-stage design with an optional refiner model.

Licenses at a glance

Apache 2.0: Z-Image-Turbo, FLUX.1 schnell. Non-commercial: FLUX.1 dev. Qwen Research License: Qwen-Image-2.1. CreativeML Open RAIL++-M: SDXL base.

Running these on Aquanode

Rent a GPU by the hour and run the pipeline with diffusers or the vendor code. See pricing and the VRAM calculator. The table below lists all text-to-image models in the catalog.