Longcat Image Text To Image

Longcat Image Text To Image

Playground

LongCat-Image is a 6B parameter bilingual (Chinese-English) text-to-image model from Meituan, excelling at multilingual text rendering, photorealism, and deployment efficiency. Ready-to-use REST inference API with best performance and no cold starts.

Features

LongCat-Image is an open-source, bilingual (Chinese-English) foundation model for image generation developed by Meituan. With only 6B parameters, it addresses key challenges in multilingual text rendering, photorealism, deployment efficiency, and developer accessibility.

Where LongCat-Image fits best

• Chinese and English text rendering in images
• Photorealistic image generation
• High-volume generation with efficient resource usage
• Marketing and product visuals with text overlays

Key Features

• Exceptional Efficiency and Performance

With only 6B parameters, LongCat-Image outperforms larger open-source models across multiple benchmarks, demonstrating efficient model design.

• Powerful Chinese Text Rendering

Superior accuracy in rendering Chinese characters with industry-leading Chinese dictionary coverage. More stable than existing SOTA open-source models.

• Remarkable Photorealism

Innovative data strategy and training framework delivers high-quality, photorealistic image generation.

• Bilingual Support

Natively supports both Chinese and English prompts with excellent text rendering in both languages.

• Resource-conscious

The efficient 6B parameter architecture keeps GPU usage moderate, ideal for batch jobs and cost-sensitive pipelines.

Related Models on WaveSpeedAI

• LongCat-Image Edit – Image editing with the same bilingual text rendering capabilities.

More Image Tools on WaveSpeedAI

• Nano Banana Pro – Google’s Gemini-based text-to-image model for sharp, coherent, prompt-faithful visuals.
• Seedream V4 – style-consistent, multi-image generator ideal for posters and campaigns.
• Qwen Edit Plus – An enhanced Qwen-based image editor for precise inpainting and local style changes.

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",
  "size": "1024*1024",
  "output_format": "jpeg",
  "seed": -1
}
JSON
)

# 1. Submit the prediction.
SUBMIT_RESPONSE=$(curl --silent --show-error --fail-with-body \
  -X POST "https://api.wavespeed.ai/api/v3/wavespeed-ai/longcat-image/text-to-image" \
  -H "Authorization: Bearer ${WAVESPEED_API_KEY}" \
  -H "Content-Type: application/json" \
  -d "${REQUEST_BODY}")

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 "${PREDICTION_ID}" ]; then
  printf 'Submission response did not contain a prediction id
' >&2
  exit 1
fi
RESULT_URL=$(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' "${RESPONSE}" | jq 'if type == "object" and has("data") then .data else . end')
  STATUS=$(printf '%s' "${RESULT}" | jq -r '.status // empty')

  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
done

Parameters

Task Submission Parameters

Request Parameters

Response Parameters

Result Request Parameters

Result Response Parameters