HiDream O1 Dev

hidream-ai/hidream-o1/dev

Hidream O1 Dev by hidream-ai - generate stunning images from text prompts with state-of-the-art AI. Supports multiple aspect ratios, styles, and high-resolution output for creative and commercial use.

Base price
$0.005 / run
Execution
async
Model type
image
Input fields
5

Try the model

Playground

Open playground
Input
Text prompt for image generation, editing, or subject-driven personalization.
The aspect ratio of the generated image. Allowed values: 21:9, 16:9, 3:2, 4:3, 5:4, 1:1, 4:5, 3:4, 2:3, 9:16.

PNG, JPEG, WebP, or GIF · 20 MiB maximum each

Optional reference images. Use none for text-to-image, one for image editing, or multiple for subject-driven personalization.
Random seed for reproducible generation.
The format of the generated image. Allowed values: jpeg, png.
OutputReady

Your output will appear here

Complete the inputs, then click Run.

Specifications

Pricing

Base price
$0.005 / run

Context & modalities

Input
Schema-defined
Output
image

Capabilities

Chat
Not supported
Vision
Not supported
Reasoning
Not supported
Structured output
Not supported
Function calling
Not supported
Audio input
Not supported

Access

Provider
HiDream
Model ID
hidream-ai/hidream-o1/dev
Execution
async
API
Unified Run API
Endpoint
/v1/run

API README

HiDream O1 Dev

HiDream O1 Dev is a distilled image foundation model that unifies text-to-image generation, instruction-based editing, and subject-driven personalization. Its pixel-level unified architecture processes text, raw image content, and task conditions together for consistent in-context visual creation.

One endpoint covers three workflows: send no reference images to create from text, one image to apply an instructed edit, or multiple images to carry subjects into a new scene. This is the O1 Dev model, distinct from the earlier HiDream I1 family.

Highlights

  • One model, three workflows. Moves between text-to-image generation, single-image instruction editing, and multi-reference personalization according to the supplied references.
  • Pixel-level unified generation. Treats text, image pixels, and task conditions in a shared token space instead of separating generation and editing into unrelated systems.
  • Subject-driven personalization. Uses multiple references to preserve a person, character, product, or visual identity while placing it in a newly described setting.
  • Long-text rendering and layout control. Creates multi-region compositions with accurate multilingual text, supporting information-dense posters, editorial layouts, and designed graphics.

Pricing

UnitPrice
Per request$0.005000

When to Use

Good fitConsider alternatives
Creating an image from text with zero referencesA specialized text-to-image route when references will never be used
Applying a natural-language change to one imagePixel-perfect masks or manual retouching
Personalizing a scene from multiple subject referencesA single-reference task with strict reference preservation
Keeping a character or product recognizable in a new settingVideo, animation, or 3D generation
Combining generation and editing behind one integrationWorkflows requiring explicit layout boxes or skeleton controls not exposed here

Prompt Guide

Match the prompt to the reference count. With no images, fully describe the scene. With one image, state exactly what should change and what must remain. With multiple images, identify the shared subject and describe the new setting, pose, camera, and identity details to preserve.

{
  "prompt": "Use the referenced ceramic mug as the exact product identity. Place it on a pale stone café table beside an open sketchbook, soft morning window light from the left, eye-level product photography, shallow depth of field. Preserve the mug's shape, glaze color, handle, and printed emblem.",
  "images": [
    "https://example.com/references/mug-front.png",
    "https://example.com/references/mug-side.png"
  ],
  "aspect_ratio": "4:3",
  "output_format": "png",
  "seed": 42
}

Technical Specs

SpecValue
Model IDhidream-ai/hidream-o1/dev
InputRequired text prompt; optional array of reference-image URLs
Reference workflow0 images: text-to-image; 1: editing; 2 or more: subject-driven personalization
Aspect ratios21:9, 16:9 (default), 3:2, 4:3, 5:4, 1:1, 4:5, 3:4, 2:3, 9:16
Output formatPNG (default) or JPEG
Optional controlsInteger seed
OutputOne downloadable image URL
ExecutionAsync

Related

Start building

Send your first request

OpenAI-compatible endpoint with unified authentication and usage tracking.

Production API
Endpoint
https://api.sandbase.ai/v1/run
Model ID
hidream-ai/hidream-o1/dev
# Preserve Unicode and shell metacharacters in the request body.
result=$(printf '%s' 'ewogICJtb2RlbCI6ICJoaWRyZWFtLWFpL2hpZHJlYW0tbzEvZGV2IiwKICAiaW1hZ2VzIjogWwogICAgImh0dHBzOi8vc3RhdGljLnNhbmRiYXNlLmFpL2V4YW1wbGVzL2hpZHJlYW0tYWkvaGlkcmVhbS1vMS9kZXYvaW5wdXRfcmVmZXJlbmNlX2ltYWdlX3VybHNfMC5wbmciCiAgXSwKICAicHJvbXB0IjogIkEgY2luZW1hdGljIHByb2R1Y3QgcGhvdG8gb2YgYSBjZXJhbWljIG11ZyBvbiBhIG1hcmJsZSBjb3VudGVyLCBzb2Z0IHdpbmRvdyBsaWdodCwgc2hhbGxvdyBkZXB0aCBvZiBmaWVsZC4iLAogICJhc3BlY3RfcmF0aW8iOiAiMTY6OSIsCiAgIm91dHB1dF9mb3JtYXQiOiAicG5nIgp9' \
  | base64 --decode \
  | curl --fail-with-body --silent \
      -X POST "https://api.sandbase.ai/v1/run" \
      -H "Authorization: Bearer $SANDBASE_API_KEY" \
      -H "Content-Type: application/json" \
      --data-binary @-)
run_id=$(printf '%s' "$result" | jq -r .id)
for attempt in $(seq 1 120); do
  status=$(printf '%s' "$result" | jq -r .status)
  case "$status" in completed|failed|timeout) break ;; esac
  sleep 2
  result=$(curl --fail-with-body --silent \
    -H "Authorization: Bearer $SANDBASE_API_KEY" \
    "https://api.sandbase.ai/v1/run/$run_id")
done
status=$(printf '%s' "$result" | jq -r .status)
[ "$status" = completed ] || { echo "Generation ended: $status" >&2; exit 1; }
printf '%s\n' "$result"

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