P H3 Image Text To Image API Documentation

P H3 Image Text To Image API Documentation

Playground

P-H3-Image by Pruna AI, built on MiniMax H3 open weights, generates photorealistic, editorial-quality images from text prompts for creative visuals, product imagery, branded content, and production workflows. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.

Features

P-H3-Image Text-to-Image generates images from text prompts using the MiniMax H3 open weights. Create photorealistic, editorial, cinematic, and creative visuals with flexible aspect ratios and output resolutions from 1k to 4k.

Why Choose This?

• High-quality image generation — Create detailed images from natural-language descriptions.
• Up to 4K output — Choose 1k, 1.5k, 2k, 3k, or 4k depending on your quality needs.
• Flexible framing — Generate images across a wide range of landscape, portrait, square, and ultrawide aspect ratios.
• Multiple output formats — Export as JPEG, PNG, or WebP.
• Seed control — Use a fixed seed for more reproducible generation.

Parameters

How to Use

1. Write a prompt — Describe the subject, setting, composition, lighting, and visual style.
2. Choose framing — Select the aspect ratio that fits your target layout.
3. Choose resolution — Use lower resolutions for iteration or higher resolutions when more detail is needed.
4. Choose output format optional — Select JPEG, PNG, or WebP.
5. Set a seed optional — Use a fixed seed when comparing prompt variations.
6. Submit — Generate and retrieve the finished image.

Pricing

Pricing is based on the selected resolution.

Aspect ratio, output format, and seed do not add separate charges.

Best Use Cases

• Photorealistic imagery — Generate people, environments, products, and lifestyle scenes.
• Editorial visuals — Create magazine-style and documentary-inspired imagery.
• Advertising concepts — Produce campaign, product, and promotional visuals.
• Cinematic concepts — Explore dramatic lighting, compositions, and scene designs.
• High-resolution assets — Generate detailed images for publishing and design workflows.

Pro Tips

• Describe the subject, setting, composition, lighting, and visual style clearly.
• Use concrete visual details instead of unnecessary descriptive language.
• Put short text that should appear in the image inside quotation marks.
• Use 3k or 4k when finer visual detail is important.
• Use a fixed seed when comparing prompt changes while keeping the generation setup consistent.

Notes

• prompt is required.
• aspect_ratio defaults to 1:1.
• resolution defaults to 1k.
• Supported resolutions are 1k, 1.5k, 2k, 3k, and 4k.
• output_format defaults to jpeg.
• Use seed=-1 for random seed selection.
• Higher resolutions increase the generation price.

Related Models

• P-H3-Image Edit — Edit existing images with P-H3-Image.
• P-H3-Image Text-to-Image LoRA — Generate images with custom LoRA guidance.
• P-H3-Image Edit LoRA — Edit images with custom LoRA guidance.
• MiniMax H3 Text-to-Video — Generate videos with the MiniMax H3 model family.

Authentication

For authentication details, please refer to the Authentication Guide.

API Endpoints

Submit Task & Query Result

set -euo pipefail

export WAVESPEED_API_KEY="your-api-key"

REQUEST_BODY=$(cat <<'JSON'
{
  "prompt": "A cinematic ocean wave at sunrise, highly detailed",
  "aspect_ratio": "1:1",
  "resolution": "1k",
  "output_format": "jpeg"
}
JSON
)

# 1. Submit the prediction once. Never retry this request automatically:
# a retry after an unclear failure can create a second, billed task.
CHECK='The task may already exist. Check History or the predictions list before submitting again.'
if ! SUBMIT_RESPONSE=$(curl --silent --show-error --fail-with-body \
  --connect-timeout 10 --max-time 60 \
  -X POST "https://api.wavespeed.ai/api/v3/wavespeed-ai/p-h3-image/text-to-image" \
  -H "Authorization: Bearer ${WAVESPEED_API_KEY}" \
  -H "Content-Type: application/json" \
  -d "${REQUEST_BODY}"); then
  printf 'Submit failed. %s\n' "${CHECK}" >&2
  exit 1
fi

TASK=$(printf '%s' "${SUBMIT_RESPONSE}" | jq 'if type == "object" and has("data") then .data else . end')
PREDICTION_ID=$(printf '%s' "${TASK}" | jq -r '.id // empty')
if [ -z "${PREDICTION_ID}" ]; then
  printf 'Submission response did not contain a prediction id. %s\n' "${CHECK}" >&2
  exit 1
fi
RESULT_URL="https://api.wavespeed.ai/api/v3/predictions/${PREDICTION_ID}/result"

# 2. Poll until the prediction reaches a final status.
BODY_FILE=$(mktemp)
trap 'rm -f "${BODY_FILE}"' EXIT
while true; do
  # Transient errors (429, 5xx) are retried, honoring Retry-After.
  HTTP_CODE=$(curl --silent --show-error --fail-with-body \
    --connect-timeout 10 --max-time 60 --retry 5 --retry-delay 2 \
    --output "${BODY_FILE}" --write-out '%{http_code}' \
    "${RESULT_URL}" \
    -H "Authorization: Bearer ${WAVESPEED_API_KEY}" || true)
  case "${HTTP_CODE}" in
    2??) ;;
    000|429|5??)  # dropped connection or temporary error: keep polling
      printf 'Task %s: HTTP %s, polling again in 10s\n' "${PREDICTION_ID}" "${HTTP_CODE}" >&2
      sleep 10; continue ;;
    *) printf 'Task %s: HTTP %s\n' "${PREDICTION_ID}" "${HTTP_CODE}" >&2
      cat "${BODY_FILE}" >&2; exit 1 ;;
  esac
  RESULT=$(jq 'if type == "object" and has("data") then .data else . end' "${BODY_FILE}")
  STATUS=$(printf '%s' "${RESULT}" | jq -r '.status // empty')

  case "${STATUS}" in
    completed) printf '%s\n' "${RESULT}" | jq '.outputs'; break ;;
    failed|cancelled|timeout|deleted)
      printf 'Task %s ended with status %s\n' "${PREDICTION_ID}" "${STATUS}" >&2
      printf '%s\n' "${RESULT}" | jq . >&2; exit 1 ;;
    *) sleep 2 ;;
  esac
done

Parameters

Task Submission Parameters

Request Parameters

Every model also accepts the global request options enable_sync_mode and enable_base64_output; see their pages for details.

Response Parameters

Result Request Parameters

Result Response Parameters