Model Details
HiDream I1 Fast turns a text prompt into a high-quality image, optimized for speed and low cost. It is the fast, distilled variant of HiDream.ai's 17-billion-parameter open image foundation model, tuned to reach state-of-the-art image quality in around 16 inference steps instead of the full step count, so it returns results in seconds at roughly a fifth of the full model's price. Give it a descriptive prompt, pick a size, and it returns one to four finished images.
## Best for - Fast, low-cost text-to-image generation where turnaround matters - Prototyping and iterating on prompts before committing to a final render - AI art, illustrations, and stylized scenes from a text description - Batch marketing and social visuals produced from a short written brief - Producing several variations at once with `num_images` (1-4)
## Choose another model when - You need maximum fidelity and the highest detail - use `hidream/i1-full`, the full-quality variant - You want to attach a custom LoRA to steer style - the Fast tier has no LoRA support; use `hidream/i1-full` - You need to edit or restyle an existing photo rather than generate from scratch - use an image-editing model - You need reliably legible in-image text for logos or signage - use a model tuned for typography - You need video - use a text-to-video or image-to-video model
## Tips - Write specific, descriptive prompts; use `negative_prompt` to exclude unwanted elements - The tier defaults to 16 steps for speed; raise `num_inference_steps` (up to 50) for higher fidelity at the cost of speed - `image_size` accepts a preset (`square_hd`, `portrait_16_9`, `landscape_4_3`, ...) or a custom {width, height} object; billing is per output megapixel, so larger images cost more - Each image in `num_images` is billed separately
```js import { modelrunner } from "@modelrunner/client";
const result = await modelrunner.subscribe("hidream/i1-fast", { input: { prompt: "a red apple on a white table, studio lighting", image_size: "square_hd", num_images: 1, output_format: "jpeg", }, }); ```



