HeyGen: Avatar IV vs Kling: Video O1
A side-by-side comparison of HeyGen: Avatar IV ($0.18 / second) and Kling: Video O1 ($0.39 / second) using current USD prices and capabilities from the api14 catalog. Both run through the same OpenAI-compatible API.
Specifications
| HeyGen: Avatar IV | Kling: Video O1 | |
|---|---|---|
| Provider | HeyGen | Kling |
| duration_seconds | $0.18 / second | $0.39 / second |
| Context window | - | - |
| Max output | - | - |
| Input | text, image, audio | text, image |
| Output | video | video |
| Tool calling | ||
| Structured output | ||
| Reasoning control | ||
| Added | Aug 24, 2026 | Apr 20, 2026 |
In depth
HeyGen: Avatar IV is a video generation model from HeyGen, and Kling: Video O1 is a video generation model from Kling. Both sit in the same category on api14, so the choice between them comes down to how each one takes input and what you need the generated video to be based on. HeyGen: Avatar IV was released by its provider on 2026-08-24, while Kling: Video O1 was released by its provider on 2026-04-20.
The clearest difference is in input modalities. HeyGen: Avatar IV accepts text, image and audio as input and produces video as output. Kling: Video O1 accepts text and image as input and also produces video as output. Neither model exposes a context length in tokens, so there is no context window figure to compare. On parameters, HeyGen: Avatar IV lists no supported parameters, while Kling: Video O1 supports max_tokens, temperature and top_p. That means Kling: Video O1 gives you sampling controls you can tune, whereas HeyGen: Avatar IV does not expose those knobs. The qualitative comparison fields are all null, so there is no stated difference in input price, output price, context size, tool support, structured output support or reasoning support between the two.
For practical selection, reach for HeyGen: Avatar IV when your source material includes audio, since audio input is something only this model of the two accepts. That makes it the natural fit for tasks where a spoken track or recorded voice needs to drive the result. Reach for Kling: Video O1 when your inputs are text and images and you want to steer generation with temperature, top_p or a max_tokens setting. If your pipeline is text-to-video or image-to-video with no audio component and you care about controlling sampling behaviour, Kling: Video O1 is the one that exposes those parameters.
Calling either model through api14 works the same way, because the gateway is OpenAI-compatible. You send your request to the same endpoint with the same request shape, and the only thing you change is the model id. Use "heygen/avatar-iv" when you want the HeyGen model, and use "kwaivgi/kling-video-o1" when you want the Kling model. Everything else in your client code, including how you authenticate and how you parse the response, stays as it is. If you are already sending audio alongside your prompt, keep the model id set to "heygen/avatar-iv"; if you are sending text and images and passing sampling parameters, set it to "kwaivgi/kling-video-o1". Switching between the two is a one line change in the model field, which makes it cheap to test both against your own inputs before committing to one.
Switch with one string
Both models use the same endpoint and request shape. Change the model value from "heygen/avatar-iv" to "kwaivgi/kling-video-o1" and prompts, streaming and tools keep working.
import OpenAI from "openai";
const client = new OpenAI({
baseURL: "https://api14.com/api/v1",
apiKey: process.env.API14_API_KEY,
});
// Video generation is asynchronous: submit, then poll until completed.
let job = await client.post("/videos", { body: {
"model": "kwaivgi/kling-video-o1",
"prompt": "A drone shot over turquoise ocean waves at sunrise",
"duration": 8,
"resolution": "720p",
"aspect_ratio": "16:9"
} });
while (!["completed", "failed"].includes(job.status)) {
await new Promise((r) => setTimeout(r, 5000));
job = await client.get(`/videos/${job.id}`);
}
console.log(job.status, job.unsigned_urls);
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