# Kling Kling v3.0 4k — Image To Video > Integrate the kling v3 api for native 4K video. Create cinematic multi-shot clips with lip-sync and physics-aware realism via GPTProto.com. Get started now. ## Overview - **Endpoint**: `POST https://gptproto.com/api/v3/kling/kling-v3.0-4k/image-to-video` - **Result URL**: `GET https://gptproto.com/api/v3/predictions/{result_id}/result` — the submit response also returns the authoritative URL in `data.urls.get` - **Model ID**: `kling-v3.0-4k` - **Vendor**: Kling - **Scene**: `image-to-video` - **Category**: image-to-video - **Modalities**: input image → output video - **Playground**: https://gptproto.com/model/kling/kling-v3.0-4k/image-to-video - **API documentation**: https://docs.gptproto.com - **Other scenes of this model**: `text-to-video` — same auth, different endpoint path and input schema ## Authentication Every request needs a GPTProto API key in the `Authorization` header. Create one at https://gptproto.com/dashboard/api-key, then export it: ```bash export GPTPROTO_API_KEY="your-api-key" ``` Header: `Authorization: Bearer $GPTPROTO_API_KEY` (plus `Content-Type: application/json` on POST). ## Pricing Platform price by tier (USD, already includes the GPTProto discount): - Cheapest tier — **3**: $1.01 per run - Most expensive tier — **15**: $7.56 per run - 52 priced tiers in total; the parameters below select the tier. - `sound`: no, yes - `duration`: 3–15 - Example — sound=no, duration=3: $1.01 - Example — sound=yes, duration=7: $3.53 - Example — sound=yes, duration=15: $7.56 Price range: $1.01 – $7.56 per generation. Prices may change. The model page always shows the live price: https://gptproto.com/model/kling/kling-v3.0-4k/image-to-video ## API Information The API is asynchronous: POST the endpoint to create a prediction, then poll its result URL until `status` is `completed` or `failed`. ### Input Schema The endpoint accepts the following JSON body parameters: - **`prompt`** (`string`, _required_): The positive prompt for the generation. - **`negative_prompt`** (`string`, _optional_): The negative prompt for the generation. - **`image`** (`string`, _required_): Supported image formats:.jpg /.jpeg /.png The size of the image file should not exceed 10MB, the width and height of the image should be no less than 300px, and the aspect ratio of the image should be between 1:2.5 and 2.5:1 - **`last_image`** (`string`, _optional_): The end image for generating the output. - **`cfg_scale`** (`range`, _optional_): Flexibility in video generation; The higher the value, the lower the model’s degree of flexibility, and the stronger the relevance to the user’s prompt. - Default: `0.5` - Range: 0–1 - **`sound`** (`enum`, _optional_): Whether sound is generated simultaneously when generating a video - Default: `false` - Options: true, false - **`duration`** (`enum`, _optional_): The duration of the generated media in seconds. - Default: `5` - Options: 5, 10 **Required Parameters Example**: ```json { "prompt": "A tiny origami fox sailing a teacup across a moonlit puddle", "image": "" } ``` **Full Example**: ```json { "prompt": "A tiny origami fox sailing a teacup across a moonlit puddle", "negative_prompt": "", "image": "", "last_image": "", "cfg_scale": 0.5, "sound": false, "duration": 5 } ``` ### Output Schema Both submit and poll return the same envelope: - **`data.id`** (`string`): Prediction id. Use it as `result_id` when polling for the result. - **`data.status`** (`string`): One of `created`, `running`, `completed`, `failed`. See Status Values below. - **`data.outputs`** (`array of string`): Generated files. Empty until `status` is `completed`; then it holds the output URLs (or base64 strings when the model exposes a base64 option). - **`data.urls.get`** (`string`): Authoritative result URL for this prediction. Prefer it over building the poll URL yourself. - **`data.error`** (`string | null`): Failure reason when `status` is `failed`, otherwise `null`. - **`data.executionTime`** (`integer`): Total processing time in milliseconds. - **`data.timings.inference`** (`integer`): Model inference time in milliseconds. - **`data.hasNsfwContents`** (`array of boolean`): Per-output moderation flags. - **`message`** (`string`): `success` on a normal response, otherwise the error message. - **`code`** (`integer`): Business status code. `200` means the request was accepted. **Example Response — submit (task accepted)**: ```json { "data": { "id": "pred_example_01", "model": "kling-v3.0-4k", "outputs": [], "urls": { "get": "https://gptproto.com/api/v3/predictions/pred_example_01/result" }, "hasNsfwContents": [], "status": "created", "createdAt": "2026-01-01T12:00:00Z", "executionTime": 0, "timings": { "inference": 0 } }, "message": "success", "code": 200 } ``` **Example Response — poll (completed)**: ```json { "data": { "id": "pred_example_01", "model": "kling-v3.0-4k", "outputs": [ "https://oss-us.gptproto.com/example/output.mp4" ], "urls": { "get": "https://gptproto.com/api/v3/predictions/pred_example_01/result" }, "status": "completed", "error": null, "executionTime": 12345, "timings": { "inference": 12000 }, "has_nsfw_contents": [], "created_at": "2026-01-01T12:00:00Z" }, "message": "success", "code": 200 } ``` ### Status Values - `created` — Task accepted. Use `data.id` as `result_id` for polling. - `running` — Generation is in progress. Keep polling. - `completed` — Finished successfully. Generated files are in `data.outputs`. - `failed` — Generation failed. Read `data.error` for the reason. ## Usage Examples ### 1. Submit a request ```bash curl --request POST "https://gptproto.com/api/v3/kling/kling-v3.0-4k/image-to-video" \ --header "Authorization: Bearer $GPTPROTO_API_KEY" \ --header "Content-Type: application/json" \ --data '{ "prompt": "A tiny origami fox sailing a teacup across a moonlit puddle", "negative_prompt": "", "image": "", "last_image": "", "cfg_scale": 0.5, "sound": false, "duration": 5 }' ``` ```python import os import requests url = "https://gptproto.com/api/v3/kling/kling-v3.0-4k/image-to-video" headers = { "Authorization": f"Bearer {os.environ['GPTPROTO_API_KEY']}", "Content-Type": "application/json" } payload = { "prompt": "A tiny origami fox sailing a teacup across a moonlit puddle", "negative_prompt": "", "image": "", "last_image": "", "cfg_scale": 0.5, "sound": False, "duration": 5 } response = requests.request("POST", url, headers=headers, json=payload) print(response.json()) ``` ```typescript const response = await fetch("https://gptproto.com/api/v3/kling/kling-v3.0-4k/image-to-video", { method: "POST", headers: { "Authorization": `Bearer ${process.env.GPTPROTO_API_KEY}`, "Content-Type": "application/json", }, body: JSON.stringify({ prompt: "A tiny origami fox sailing a teacup across a moonlit puddle", negative_prompt: "", image: "", last_image: "", cfg_scale: 0.5, sound: false, duration: 5, }), }); const data = await response.json(); console.log(data); ``` ### 2. Poll until the task finishes Replace `YOUR_RESULT_ID` with `data.id` from the submit response (or call `data.urls.get` directly), and keep polling every 1–3 seconds while `status` is `created` or `running`. ```bash result_id="YOUR_RESULT_ID" curl --request GET "https://gptproto.com/api/v3/predictions/$result_id/result" \ --header "Authorization: Bearer $GPTPROTO_API_KEY" ``` ```python import os import requests result_id = "YOUR_RESULT_ID" url = f"https://gptproto.com/api/v3/predictions/{result_id}/result" headers = { "Authorization": f"Bearer {os.environ['GPTPROTO_API_KEY']}" } response = requests.request("GET", url, headers=headers) print(response.json()) ``` ```typescript const result_id = "YOUR_RESULT_ID"; const response = await fetch(`https://gptproto.com/api/v3/predictions/${result_id}/result`, { method: "GET", headers: { "Authorization": `Bearer ${process.env.GPTPROTO_API_KEY}`, }, }); const data = await response.json(); console.log(data); ``` ## Example Prompts - Close-up shot, the craftsman is fully focused on assembling a complex brass machine. His right hand holding the tool carefully turns a component, and the small gears inside the machine rotate slowly in response. Faint steam or smoke drifts in the background. The metal surfaces re… - Pages fly out from the shelves and spiral into the portal. The student reaches for one floating page, the library clock spins backward, and the camera rotates slightly as the room bends around him. - He lifts the noodles with chopsticks as steam curls around his face. Raindrops slide down the window, neon signs blink outside, and the camera shifts from the ramen bowl to his tired expression. ## HTTP Status Codes - `400` — malformed body, a parameter or value this model does not accept, or input blocked by the provider's content moderation - `401` — missing or invalid API key - `403` — insufficient credits - `413` — request body too large - `429` — rate limited; retry with backoff - `500` — An internal server error occurred - `502` — An internal server error occurred - `504` — Gateway timeout — upstream service did not respond in time; retry later ## Additional Resources - [Model playground](https://gptproto.com/model/kling/kling-v3.0-4k/image-to-video) - [API documentation](https://docs.gptproto.com) - [All models](https://gptproto.com/model) - [API keys](https://gptproto.com/dashboard/api-key) - [Platform overview for LLMs](https://gptproto.com/llm-full.txt) - Any other model: `https://gptproto.com/model/{vendor}/{model}/{scene}/llms.txt`