HiDream-O1-Image Dev is a distilled, faster variant of the unified HiDream-O1-Image model — same native text-to-image / edit / personalization architecture at up to 2K, optimized for low-step inference and lower cost. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.
Idle

$0.02per run·~50 / $1

A clean isometric illustration of a computer architecture system, CPU, memory, storage, and accelerator modules connected by glowing data paths, minimal academic style, white background, precise layout, professional technical visualization

A massive near-future data center interior, rows of liquid-cooled server racks glowing with soft cyan light, robotic maintenance arms, reflective polished floor, cinematic volumetric lighting, ultra-detailed industrial design, realistic materials, wide-angle shot, high contrast, 8k, photorealistic

A calm female commander in futuristic tactical armor, standing in a holographic command room, short black hair, focused expression, subtle battle scars, cinematic lighting, realistic fabric and metal textures, highly detailed character design, medium shot
HiDream-O1-Image Dev is the distilled variant of HiDream-O1-Image. It keeps the unified, single-native-model architecture (text-to-image, image editing, and subject-driven personalization) and the same up to 2K (≈2048×2048) resolution ceiling, but is tuned for fast, low-step inference — making it the best pick when you need speed and lower cost without giving up the HiDream-O1 look.
seed to recreate exact results.| Parameter | Required | Description |
|---|---|---|
| prompt | Yes | Text description of the image you want to generate. |
| size | No | Output image size as WIDTH*HEIGHT (default: 2048*2048). The model snaps to the closest supported resolution. |
| output_format | No | Output format: jpeg, png, or webp (default: jpeg). |
| seed | No | Random seed for reproducible generation. |
| enable_sync_mode | No | API only — wait for the result and return it inline. |
| enable_base64_output | No | API only — return the image as a base64 string instead of a URL. |
size — pick an aspect ratio that fits your use case (e.g., 2048*2048 for square, 1536*2048 for portrait, 2048*1152 for landscape).output_format — JPEG for compact files, PNG for lossless, WEBP for balance.seed (optional) — pin a number to reproduce exact results.Flat rate per generated image — half the price of the full HiDream-O1-Image model.
| Output | Cost |
|---|---|
| Per image | $0.02 |
| HiDream-O1-Image Dev | HiDream-O1-Image (Full) | |
|---|---|---|
| Speed | Faster (distilled, fewer steps) | Standard |
| Cost / image | $0.02 | $0.04 |
| Quality ceiling | High | Highest |
| Best for | Drafts, batches, low-cost generation | Final, hero images |
Use Dev when you're iterating, batching, or cost-sensitive. Switch to the full model for the very best fidelity on hero shots.
seed while iterating so you can A/B test prompt tweaks against a fixed baseline.size to your final use case (square for thumbnails, 16:9 for banners, 9:16 for mobile).png when you need lossless quality; use jpeg or webp to keep file sizes small.prompt is required — every other field is optional.Grab a WaveSpeedAI API key, then call POST https://api.wavespeed.ai/api/v3/wavespeed-ai/hidream-o1-image-dev/text-to-image with your input as JSON. The endpoint returns a prediction id. Start polling the result endpoint around every 2 seconds, increase the interval for long-running tasks, and stop on any terminal status. On completed, read output values from data.outputs. Examples for Hidream O1 Image Dev Text To Image below.
set -euo pipefail
: "${WAVESPEED_API_KEY:?Set WAVESPEED_API_KEY}"
REQUEST_BODY=$(cat <<'JSON'
{
"prompt": "A cinematic shot of a city at sunset, soft golden light",
"size": "2048*2048",
"output_format": "jpeg"
}
JSON
)
# 1. Submit the prediction.
SUBMIT_RESPONSE=$(curl --silent --show-error --fail-with-body \
-X POST "https://api.wavespeed.ai/api/v3/wavespeed-ai/hidream-o1-image-dev/text-to-image" \
-H "Content-Type: application/json" \
-H "Authorization: Bearer $WAVESPEED_API_KEY" \
-d "$REQUEST_BODY")
TASK=$(printf '%s' "$SUBMIT_RESPONSE" | jq 'if has("data") then .data else . end')
PREDICTION_ID=$(printf '%s' "$TASK" | jq -r '.id')
if [ -z "$PREDICTION_ID" ] || [ "$PREDICTION_ID" = "null" ]; then
printf 'Submission response did not contain a prediction id
' >&2
exit 1
fi
RESULT_URL=$(printf '%s' "$TASK" | jq -r '.urls.get // empty')
if [ -z "$RESULT_URL" ]; then
RESULT_URL="https://api.wavespeed.ai/api/v3/predictions/$PREDICTION_ID/result"
fi
# 2. Poll until the prediction finishes.
while true; do
RESPONSE=$(curl --silent --show-error --fail-with-body "$RESULT_URL" \
-H "Authorization: Bearer $WAVESPEED_API_KEY")
RESULT=$(printf '%s' "$RESPONSE" | jq 'if has("data") then .data else . end')
STATUS=$(printf '%s' "$RESULT" | jq -r '.status')
case "$STATUS" in
completed) printf '%s\n' "$RESULT" | jq '.outputs'; break ;;
failed|cancelled|timeout) printf '%s\n' "$RESULT" | jq . >&2; exit 1 ;;
created|processing) sleep 2 ;;
*) printf 'Unexpected status: %s
' "$STATUS" >&2; exit 1 ;;
esac
doneconst submitUrl = "https://api.wavespeed.ai/api/v3/wavespeed-ai/hidream-o1-image-dev/text-to-image";
const apiKey = process.env.WAVESPEED_API_KEY;
if (!apiKey) throw new Error('Set WAVESPEED_API_KEY');
async function requestJson(url, options = {}) {
const response = await fetch(url, options);
if (!response.ok) throw new Error(await response.text());
return response.json();
}
// 1. Submit the prediction.
const body = await requestJson(submitUrl, {
method: "POST",
headers: {
"Authorization": `Bearer ${apiKey}`,
"Content-Type": "application/json",
},
body: JSON.stringify({
"prompt": "A cinematic shot of a city at sunset, soft golden light",
"size": "2048*2048",
"output_format": "jpeg"
}),
});
const task = body.data ?? body;
if (!task.id) throw new Error("Submission response did not contain a prediction id");
const resultUrl = task.urls?.get ||
`https://api.wavespeed.ai/api/v3/predictions/${task.id}/result`;
// 2. Poll until the prediction finishes.
while (true) {
const resultBody = await requestJson(resultUrl, {
headers: { "Authorization": `Bearer ${apiKey}` },
});
const result = resultBody.data ?? resultBody;
if (result.status === "completed") {
console.log(result.outputs);
break;
}
if (["failed", "cancelled", "timeout"].includes(result.status)) throw new Error(JSON.stringify(result));
if (!["created", "processing"].includes(result.status)) throw new Error("Unexpected status: " + result.status);
await new Promise(resolve => setTimeout(resolve, 2000));
}import json
import os
import time
from urllib.request import Request, urlopen
api_key = os.environ["WAVESPEED_API_KEY"]
headers = {"Authorization": f"Bearer {api_key}", "Content-Type": "application/json"}
payload = {
"prompt": "A cinematic shot of a city at sunset, soft golden light",
"size": "2048*2048",
"output_format": "jpeg"
}
def request_json(url, data=None):
request = Request(url, data=data, headers=headers, method="POST" if data else "GET")
with urlopen(request) as response:
return json.load(response)
# 1. Submit the prediction.
body = request_json("https://api.wavespeed.ai/api/v3/wavespeed-ai/hidream-o1-image-dev/text-to-image", json.dumps(payload).encode())
task = body.get("data", body)
if not task.get("id"):
raise RuntimeError("Submission response did not contain a prediction id")
result_url = task.get("urls", {}).get("get") or f"https://api.wavespeed.ai/api/v3/predictions/{task['id']}/result"
# 2. Poll until the prediction finishes.
while True:
result_body = request_json(result_url)
result = result_body.get("data", result_body)
status = result.get("status")
if status == "completed":
print(result.get("outputs", []))
break
if status in {"failed", "cancelled", "timeout"}:
raise RuntimeError(result)
if status not in {"created", "processing"}:
raise RuntimeError(f"Unexpected status: {status}")
time.sleep(2)Hidream O1 Image Dev Text To Image is a WaveSpeedAI model for image generation, exposed as a REST API on WaveSpeedAI. HiDream-O1-Image Dev is a distilled, faster variant of the unified HiDream-O1-Image model — same native text-to-image / edit / personalization architecture at up to 2K, optimized for low-step inference and lower cost. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing. You can call it programmatically or try it from the playground above.
POST your input parameters to the model's REST endpoint (shown in the API tab of this playground) with your WaveSpeedAI API key in the Authorization header. Submission returns a prediction ID. Poll the result endpoint starting around every 2 seconds, increase the interval for long-running tasks, and stop on any terminal status. The playground generates production-oriented Python, JavaScript, and cURL examples with timeouts, transient-error handling, and safe GET retries. Full request/response shape is documented at https://wavespeed.ai/docs/docs-api/wavespeed-ai/hidream-o1-image-dev-text-to-image.
Hidream O1 Image Dev Text To Image starts at $0.020 per run. That figure is the base price — the final charge scales with the parameters you set in the form (output size, length, count, references, or whatever knobs this model exposes), so a higher-quality or larger output costs more than a minimal one. The exact cost for your current input is shown live next to the Generate button before you submit, and the actual per-call charge is recorded on the prediction afterwards.
Key inputs: `prompt`, `size`, `enable_base64_output`, `enable_sync_mode`, `output_format`. The full JSON schema (types, defaults, allowed values) is rendered above the Generate button and mirrored in the API reference at https://wavespeed.ai/docs/docs-api/wavespeed-ai/hidream-o1-image-dev-text-to-image.
Median end-to-end generation time on WaveSpeedAI is around 14 seconds per request, based on recent successful runs. Queue time varies with global demand; live status is visible in the prediction record.
Commercial usage rights depend on the model's license, set by its provider (WaveSpeedAI). The license summary appears on the model card above; see WaveSpeedAI's Terms of Service for platform-level conditions.