Kling Image O1

Kling Image O1 is an image model for text-to-image generation, single-image editing, multiple-image references, and image-set output, with resolution options up to 4K. It is suited to product visuals, advertising assets, concept design, image editing, and automated creative workflows that need repeatable API access. Use the playground below to test representative prompts, reference images, dimensions, quality settings, output formats, and image counts that are available for this model. Before production rollout, compare visual quality, instruction following, subject consistency, processing time, failure handling, and estimated cost with your actual workload. The controls shown on this page describe the currently supported integration options.

An editorial design still life with a white sculptural chair, red fabric, pottery, and plants

Model ID: kling-image-o1
Provider: Kling
API endpoint: /v1/images/tasks
Pricing: 0.029411764706
Last updated: 2026-08-13

Capabilities

Image generation through the current public endpoint
Editing or reference-image controls when exposed by the live schema
Current parameters including prompt, task_type, operation

Limitations

Capabilities and parameter ranges can change; pin and validate the parameter set used in production
Do not assume support for parameters absent from the live request schema
Asynchronous jobs require explicit polling, failure, timeout, and safety-status handling

Use cases

Product prototypes and automated content workflows
Batch media generation and programmatic creative tooling
Multi-model applications that need unified authentication, billing, and usage records

Pricing and billing examples

1K/2K image output | 0.029411764706 | output_images | {"operation":["image.generate","image.edit"],"resolution_tier":["default","1k","2k"]}
4K image output | 0.058823529412 | output_images | {"operation":["image.generate","image.edit"],"resolution_tier":"4k"}

Request parameters

Parameter	Type	Required	Default	Options
model	string	Yes
prompt	textarea	Yes
task_type	select	Yes	text2image	text2image, image2image
operation	select	Yes	text_to_image	text_to_image, image_edit, reference_to_image
resolution	select	Yes	1k	1k, 2k, 4k
aspect_ratio	select	No	16:9	auto, 16:9, 9:16, 1:1, 4:3, 3:4, 3:2, 2:3, 21:9
image	asset_list	No
image_urls	asset_list	No
num_images	integer	No	1
result_type	select	No	single	single, series
watermark	boolean	No	false

API examples

cURL

curl -X POST 'https://api.uniall.ai/v1/images/tasks' \
  -H 'Authorization: Bearer $UNIALL_API_KEY' \
  -H 'Content-Type: application/json' \
  -d '{"aspect_ratio":"16:9","model":"kling-image-o1","num_images":1,"operation":"text_to_image","prompt":"Describe the output you want","resolution":"1k","result_type":"single","task_type":"text2image","watermark":false}'

Python

import json
import requests

payload = json.loads(r'''{"aspect_ratio":"16:9","model":"kling-image-o1","num_images":1,"operation":"text_to_image","prompt":"Describe the output you want","resolution":"1k","result_type":"single","task_type":"text2image","watermark":false}''')
response = requests.post(
    "https://api.uniall.ai/v1/images/tasks",
    headers={"Authorization": "Bearer " + UNIALL_API_KEY},
    json=payload,
)
response.raise_for_status()
result = response.json()

JavaScript

const response = await fetch("https://api.uniall.ai/v1/images/tasks", {
  method: 'POST',
  headers: {
    Authorization: `Bearer ${process.env.UNIALL_API_KEY}`,
    'Content-Type': 'application/json',
  },
  body: JSON.stringify({"aspect_ratio":"16:9","model":"kling-image-o1","num_images":1,"operation":"text_to_image","prompt":"Describe the output you want","resolution":"1k","result_type":"single","task_type":"text2image","watermark":false}),
});

if (!response.ok) throw new Error(`HTTP ${response.status}`);
const result = await response.json();

Frequently asked questions

What API endpoint does kling-image-o1 use?

The endpoint is resolved from the current model capabilities and request schema and shown on this page.

How is kling-image-o1 priced?

The pricing section reads the current structured billing configuration, so editorial text does not need a rewrite after a price change.

Can I use Python?

Yes. The example uses the current endpoint and exact model identifier.

Are JavaScript and cURL examples included?

Yes. All examples share the same live request structure.

Which resolution, duration, or reference-image controls are supported?

Supported controls come from the current request schema. Do not assume fields that are not listed.

What should I validate before production use?

Validate parameters, timeouts, error handling, and asynchronous generation status behavior after model updates.