Z Image Base

Z Image Base

Playground

Try it on WaveSpeedAI!

Z-Image-Base is a 6 billion-parameter text-to-image model with full CFG support. Supports fine-tuning capabilities for maximum control over image generation. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.

Features

Z-Image Base is a 6-billion parameter text-to-image model from Tongyi-MAI that generates photorealistic images with optional reference image guidance. Provide a text prompt alone, or add a reference image to guide the composition, style, or subject — all at an incredibly affordable price.


Why Choose This?

  • Reference image guidance Optionally provide a reference image to influence the generated output’s composition, style, or subject matter.

  • Flexible output sizing Customize width and height up to 1024px for any aspect ratio you need.

  • Strength control Fine-tune how much the reference image influences the output with the strength parameter.

  • Prompt Enhancer Built-in tool to automatically improve your prompts for better results.

  • Ultra-affordable Just $0.01 per image — perfect for high-volume generation and experimentation.


Parameters

ParameterRequiredDescription
promptYesText description of the image you want to generate
imageNoReference image to guide generation (upload or URL)
sizeNoPreset size options
widthNoOutput width in pixels (default: 1024)
heightNoOutput height in pixels (default: 1024)
strengthNoHow much the reference image influences output, 0-1 (default: 0.6)
seedNoRandom seed for reproducibility (default: -1 for random)
output_formatNoOutput format: jpeg, png (default: jpeg)
enable_sync_modeNoAPI only: wait for result before returning response

Strength Guide (with Reference Image)

  • Lower values (0.2-0.4): Strong reference influence, output closely follows the reference image
  • Medium values (0.5-0.7): Balanced blend of reference and prompt
  • Higher values (0.8-1.0): Prompt dominates, reference serves as loose inspiration

How to Use

Text-to-Image (No Reference)

  1. Write your prompt — describe the image you want to create.
  2. Set dimensions — adjust width and height for your needs.
  3. Run — submit and download your image.

With Reference Image

  1. Upload a reference image — to guide the generation’s composition or style.
  2. Write your prompt — describe the desired output.
  3. Adjust strength — control how much the reference influences the result.
  4. Run — submit and download your generated image.

Pricing

OutputCost
Per image$0.01

Best Use Cases

  • Rapid Prototyping — Generate multiple concepts quickly at minimal cost.
  • Style-guided Generation — Use reference images to maintain consistent aesthetics.
  • Content Creation — Produce visuals for social media, blogs, and marketing.
  • Creative Exploration — Experiment freely with different prompts and settings.
  • Batch Generation — Create large volumes of images affordably.

Pro Tips

  • Use the Prompt Enhancer to automatically improve your descriptions.
  • For pure text-to-image, be specific about style, lighting, and composition.
  • When using a reference image, start with strength around 0.6 and adjust based on results.
  • Keep the same seed to iterate on a specific composition while tweaking the prompt.
  • Lower strength values make output follow the reference more closely; higher values give the prompt more creative freedom.

Notes

  • When no image is provided, the model runs in pure text-to-image mode.
  • The strength parameter only applies when a reference image is provided.
  • enable_sync_mode is only available through the API, not in the web interface.

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",
  "strength": 0.6,
  "seed": -1,
  "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/z-image/base" \
  -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

ParameterTypeRequiredDefaultRangeDescription
promptstringYes-The positive prompt for the generation.
imagestringNo-URL of the reference image to guide the generation.
sizestringNo1024*1024-The size of the generated media in pixels (width*height).
strengthnumberNo0.60 ~ 1Controls the strength of the transformation. Higher values produce outputs more different from the input image.
seedintegerNo-1-The random seed to use for the generation. -1 means a random seed will be used.
output_formatstringNojpegjpeg, png, webpThe format of the output image.
enable_sync_modebooleanNofalse-If set to `true`, the request attempts to wait for the generated result and return outputs in the same response. If the result is not ready within the sync wait window, the API can return a timeout body while the task continues processing. This option is only available via the API and is supported only by some models.
enable_base64_outputbooleanNofalse-If set to `true`, the prediction's `output` strings are returned as **naked base64** (no `data:<mime>;base64,` prefix). When `false` (default), outputs are returned as URLs pointing to our CDN.

Response Parameters

ParameterTypeDescription
codeintegerHTTP status code (e.g., 200 for success)
messagestringStatus message (e.g., “success”)
data.idstringUnique identifier for the prediction, Task Id
data.modelstringModel ID used for the prediction
data.outputsarrayOutput values, usually URL strings; some models return text strings or structured result objects (empty when status is not completed)
data.urlsobjectObject containing related API endpoints
data.urls.getstringURL to retrieve the prediction result
data.statusstringStatus of the task: created, processing, completed, or failed
data.created_atstringISO timestamp of when the request was created (e.g., “2023-04-01T12:34:56.789Z”)
data.errorstringError message (empty if no error occurred)
data.timingsobjectObject containing timing details
data.timings.inferenceintegerInference time in milliseconds

Result Request Parameters

ParameterTypeRequiredDefaultDescription
idstringYes-Task ID

Result Response Parameters

ParameterTypeDescription
codeintegerHTTP status code (e.g., 200 for success)
messagestringStatus message (e.g., “success”)
dataobjectThe prediction data object containing all details
data.idstringUnique identifier for the prediction
data.modelstringModel ID used for the prediction
data.outputsarray<string | object>Array of generated outputs (empty when status is not completed). Items are usually URL strings, but may be text strings or structured result objects, depending on the model.
data.urlsobjectObject containing related API endpoints
data.urls.getstringURL to poll for the prediction result
data.statusstringStatus: created, processing, completed, or failed
data.created_atstringISO timestamp of when the request was created
data.errorstringError message (empty if no error occurred)
data.timingsobjectObject containing timing details
data.timings.inferenceintegerInference time in milliseconds
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