# Kling Image O1

> Run Kling Image O1 by klingai online or via API. $0.028/run, no setup.

**URL:** https://inference.sh/apps/klingai/image-o1
**Last updated:** 2026-08-07

---

Kling Image O1 (Kolors Image-O1) - omni image generation with element control. Text-to-image and image-to-image at 1K/2K. $0.028/image.

- app: `klingai/image-o1`
- maker: [klingai](https://inference.sh/apps/klingai.md)
- category: [image](https://inference.sh/apps/category/image.md)
- input → output: text → image, image → image
- tasks: [text to image](https://inference.sh/apps/tag/text-to-image.md), [image to image](https://inference.sh/apps/tag/image-to-image.md)
- price: $0.028/run
- runs via: api, javascript and python sdk, belt cli, mcp

## image-o1 API Guide

### About
kling image o1 (kolors image-o1) - omni image generation with element control. text-to-image and image-to-image at 1k/2k. $0.028/image.

### Get an API Key
Create one in [settings → api keys](https://app.inference.sh/settings/keys). The examples read it from `INFERENCE_API_KEY`.

```bash
export INFERENCE_API_KEY="inf_your_key"
```

### 1. Calling the API

#### Install the Client

```bash
pip install inferencesh
```

#### Run and Get Result
Submit a request and wait for the final result.

```python
import os
from inferencesh import inference

client = inference(api_key=os.environ["INFERENCE_API_KEY"])

## version @0pbaxv40 pinned
result = client.run({
        "app": "klingai/image-o1@0pbaxv40",
        "input": {
            "prompt": "prompt"
        }
    })

print(result["output"])
```

#### Stream Live Updates
Get real-time progress updates as the task runs.

```python
import os
from inferencesh import inference

client = inference(api_key=os.environ["INFERENCE_API_KEY"])

## version @0pbaxv40 pinned
## stream=True yields updates as they arrive
for update in client.run({
        "app": "klingai/image-o1@0pbaxv40",
        "input": {
            "prompt": "prompt"
        }
    }, stream=True):
    if update.get("progress"):
        print(f"progress: {update['progress']}%")
    if update.get("output"):
        print(f"output: {update['output']}")
```

#### Run in the Background
Start the task and get its id back right away, then check on it with `GET /tasks/{id}`. It is done when `status` is 10 (completed), 11 (failed) or 12 (cancelled).

```python
import os
from inferencesh import inference, TaskStatus

client = inference(api_key=os.environ["INFERENCE_API_KEY"])

## returns as soon as the task is created
task = client.run({
        "app": "klingai/image-o1@0pbaxv40",
        "input": {
            "prompt": "prompt"
        }
    }, wait=False)

## later: read its current state
state = client.tasks.get(task["id"]).data
if state["status"] == TaskStatus.COMPLETED:
    print(state["output"])
```

### 2. Files

#### Automatic Upload

```python
## local file paths are automatically uploaded
result = client.run({
    "app": "klingai/image-o1@0pbaxv40",
    "input": {
        "image": "/path/to/local/image.png",  # detected & uploaded
        "audio": "https://example.com/audio.mp3",  # url passed through
    }
})
```

#### Manual Upload

```python
## upload and get a hosted URL
file = client.files.upload("/path/to/file.png")
print(file.uri)  # https://cloud.inference.sh/...
```

### 3. Schema

#### Input
- **prompt** (string) *required*: Text description. Max 2500 chars.
- **image** (string): Reference image for image-to-image or element control.
- **negative_prompt** (string): What to avoid.
- **aspect_ratio** (string): Output aspect ratio.
- **resolution** (string): Output resolution (1K or 2K).
- **n** (integer): Number of images (1-9).

#### Output
- **image** (string): Generated image.

## other image apps

- [Gemini Nano Banana 2.1](https://inference.sh/apps/google/gemini-nano-banana-2-1.md): $1.50/M input, $0.0336–$0.1134/image (1K–4K), +$0.014/query Google Search
- [Grok Imagine Image 2.0](https://inference.sh/apps/xai/grok-imagine-image-2-0.md): $0.04/img low 1k, $0.06/img low 2k, $0.06/img med 1k, $0.08/img med 2k; $0.01/source img (edits)
- [GPT Image 2.5 Sunburst](https://inference.sh/apps/openai/gpt-image-2-5-sunburst.md): $0.006-$0.21 per 1024x1024 image: low $0.006, medium $0.013, high $0.053, xhigh $0.094, max $0.21. Larger sizes cost more; edits add ~$0.008 per reference image.
- [GPT Image 2.5 Flare](https://inference.sh/apps/openai/gpt-image-2-5-flare.md): $0.006-$0.21/image at 1024x1024: low $0.0059, medium $0.0132, high $0.0527, xhigh $0.0937, max $0.2107. Larger sizes cost more; edits add ~$0.0083 per reference image.
- [Image Resize & Crop](https://inference.sh/apps/eval/resize.md): from $0.00000277/sec

## faq

### how much does Kling Image O1 cost?

$0.028/run. you pay per run from your inference shell credits. no subscription is required.

### how do I run Kling Image O1 via api?

call klingai/image-o1 with the javascript or python sdk, the rest api, or `belt app run klingai/image-o1` from a terminal. the api reference on this page lists every input.

### who makes Kling Image O1?

Kling Image O1 is made by klingai and runs on inference shell. every klingai app is listed at https://inference.sh/apps/klingai.

### can my agent use Kling Image O1?

yes. agents call it as a tool through the inference shell mcp server (https://api.inference.sh/mcp), the belt cli or the sdk, and pay per run like you do.

### what are the alternatives to Kling Image O1?

other image apps on inference shell include Gemini Nano Banana 2.1, Grok Imagine Image 2.0, GPT Image 2.5 Sunburst, GPT Image 2.5 Flare. they run through the same api, so switching is a one-line change.