Home/Explore/WaveSpeed/P H3 Image/Text To Image Lora

P-H3-Image Text-to-Image LoRA API

wavespeed-ai/p-h3-image/text-to-image-lora

P-H3-Image by Pruna AI, built on the MiniMax H3 open weights, turns a text prompt into a photorealistic, editorial-quality image, at 1K to 4K resolution. Loads up to 3 custom LoRA weights per request. Ready-to-use REST inference API, best performance, no cold starts, affordable pricing.

Text to Image
Input

Idle

Cinematic portrait of a young man with short dark hair and light stubble in a navy wool coat, waiting at a foggy Lisbon tram stop at dawn, warm streetlight, 50mm lens, shallow depth of field, film grain.

$0.02per run·~50 / $1

ExamplesView all

Cinematic portrait of a young man with short dark hair and light stubble in a navy wool coat, waiting at a foggy Lisbon tram stop at dawn, warm streetlight, 50mm lens, shallow depth of field, film grain.

Cinematic portrait of a young man with short dark hair and light stubble in a navy wool coat, waiting at a foggy Lisbon tram stop at dawn, warm streetlight, 50mm lens, shallow depth of field, film grain.

Related Models

README

P-H3-Image Text-to-Image LoRA

P-H3-Image is Pruna AI's image generation and editing model built on the MiniMax H3 open weights. This endpoint turns a text prompt into a photorealistic, editorial-quality image from 1K up to 4K. Load up to 3 custom LoRA weights per request.

Powered by MiniMax H3.

Why Choose This?

  • LoRA support
    Load up to 3 LoRA weights per request, each with its own scale, for custom styles, characters and products.

  • Photorealistic by default
    Natural skin, light and materials, with strong prompt adherence for documentary, editorial and cinematic looks.

  • Up to 4K output
    Choose 1k, 1.5k, 2k, 3k or 4k; 3k sits closest to the model's sweet spot for fine detail.

  • Built-in prompt enhancement
    Short requests are expanded into detailed prompts automatically, so a one-line idea still renders well.

Parameters

ParameterRequiredDescription
promptYesText description of the image.
aspect_ratioNoOutput aspect ratio: 1:1, 1:2, 2:1, 1:3, 3:1, 2:3, 3:2, 3:4, 4:3, 4:5, 5:4, 9:16, 16:9, 9:21, 21:9. Defaults to 1:1.
resolutionNoOutput resolution: 1k (default, ~1 MP), 1.5k (~2.4 MP), 2k (~4 MP), 3k (~9.4 MP) or 4k (~16.8 MP).
output_formatNojpeg (default), png or webp.
lorasNoUp to 3 LoRA weights. Each item uses {path, scale}, where path is a LoRA file URL.
seedNoRandom seed. -1 picks a random seed.

How to Use

  1. Write your prompt — Describe subject, setting, lighting and style.
  2. Choose aspect ratio and resolution — 1k–2k for iteration, 3k or 4k for final assets.
  3. Submit — Receive the image URL.

Pricing

Pricing is based on the selected resolution, plus a flat $0.015 per image for LoRA support (already included below).

ResolutionCost per image
1k$0.035
1.5k$0.055
2k$0.075
3k$0.115
4k$0.175

Pro Tips

  • Start LoRA scale around 0.8–1.0, then adjust based on how strongly the LoRA affects the result.
  • Describe the scene concretely (subject, setting, light, lens); avoid hype words, which tend to make images worse.
  • Short quoted text such as a sign or a title renders well; long or small text is less reliable.
  • Use 3k or 4k for hands, small background figures and fine textures.
  • Fix the seed to iterate on wording without changing the composition.

Related Models

Reference

Note:This website uses AI models provided by third parties. Documentation prices are for reference and may be outdated. The Generate button shows an estimate; the final task charge prevails.

P H3 Image Text To Image Lora API — Quick start

Grab a WaveSpeedAI API key, then call POST https://api.wavespeed.ai/api/v3/wavespeed-ai/p-h3-image/text-to-image-lora 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 P H3 Image Text To Image Lora below.

HTTP example
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",
    "aspect_ratio": "1:1",
    "resolution": "1k",
    "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/p-h3-image/text-to-image-lora" \
  -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="https://api.wavespeed.ai/api/v3/predictions/$PREDICTION_ID/result"

# 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' "$RESULT" | jq '.outputs'; break ;;
    failed|cancelled|timeout|deleted) printf '%s\n' "$RESULT" | jq . >&2; exit 1 ;;
    *) sleep 2 ;;
  esac
done
Node.js example
const submitUrl = "https://api.wavespeed.ai/api/v3/wavespeed-ai/p-h3-image/text-to-image-lora";
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 ${apiKey}`,
    "Content-Type": "application/json",
  },
  body: JSON.stringify({
        "prompt": "A cinematic shot of a city at sunset, soft golden light",
        "aspect_ratio": "1:1",
        "resolution": "1k",
        "output_format": "jpeg"
}),
});
const task = body.data ?? body;
if (!task.id) throw new Error("Submission response did not contain a prediction id");
const resultUrl = `https://api.wavespeed.ai/api/v3/predictions/${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", "deleted"].includes(result.status)) throw new Error(JSON.stringify(result));
  await new Promise(resolve => setTimeout(resolve, 2000));
}
Python example
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",
    "aspect_ratio": "1:1",
    "resolution": "1k",
    "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/p-h3-image/text-to-image-lora", 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 = 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", "deleted"}:
        raise RuntimeError(result)
    time.sleep(2)

P H3 Image Text To Image Lora API — Frequently asked questions

What is the P H3 Image Text To Image Lora API?

P H3 Image Text To Image Lora is a WaveSpeedAI model for image generation, exposed as a REST API on WaveSpeedAI. P-H3-Image by Pruna AI, built on the MiniMax H3 open weights, turns a text prompt into a photorealistic, editorial-quality image, at 1K to 4K resolution. Loads up to 3 custom LoRA weights per request. Ready-to-use REST inference API, best performance, no cold starts, affordable pricing. You can call it programmatically or try it from the playground above.

How do I call the P H3 Image Text To Image Lora API?

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 Python, JavaScript, and cURL examples for submitting requests and polling results. Full request/response shape is documented at https://wavespeed.ai/docs/docs-api/wavespeed-ai/p-h3-image-text-to-image-lora.

How much does P H3 Image Text To Image Lora cost per run or per second?

P H3 Image Text To Image Lora starts at $0.02 per run or per second. 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.

What inputs does P H3 Image Text To Image Lora accept?

Key inputs: `prompt`, `aspect_ratio`, `resolution`, `seed`, `loras`, `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/p-h3-image-text-to-image-lora.

How do I get started with the P H3 Image Text To Image Lora API?

Sign up for a free WaveSpeedAI account to claim starter credits, copy your API key from /accesskey, then call the endpoint shown in the API tab of the playground. The playground also auto-generates a code sample in Python, JavaScript, or cURL for the parameters you've set.

Can I use P H3 Image Text To Image Lora outputs commercially?

Commercial usage rights depend on the model's license, set by its provider (WaveSpeedAI). Check the provider's applicable terms and WaveSpeedAI's Terms of Service before commercial use.

llms.txt — wavespeed-ai/p-h3-image/text-to-image-lora for AI agents and LLMs