Best AI Video APIs 2026: Seedance vs Kling vs Veo vs Wan

The best AI video generation API in 2026 depends on the job: Seedance 2.5 for long single takes (up to 30 seconds) with audio, Kling 3.0 for scenes with several shots up to 15 seconds and 4K, Veo 3.1 for polished 8-second clips at up to 4K with always-on audio, and Wan 3.0 for clips up to 30 seconds at up to 4K at a low per-second rate. All four run through the same AI video API on Jantaris, with one key and one prepaid balance. Seedance, Kling and Wan bill per second of output, Veo per 8-second clip, so the real cost follows from length and resolution.

I run all of these through one API in my own projects, and below is how they actually differ from a developer's seat, plus code to test them side by side on your own prompts.

AI video API comparison table

Specs come from the Jantaris model schemas and each vendor's official documentation as of October 2026. Where a vendor's own API allows more than Jantaris does, I say so.

The exact allowed values per model come from GET /v1/models/{id} in the input_schema field. Mind the case: Wan takes resolutions as 720P, while Seedance, Kling and Veo use 720p.

Seedance 2.5: best for long single takes

Seedance 2.5 is the one I reach for when a scene needs to breathe. Thirty seconds in one generation means one continuous shot with consistent lighting and characters, no cuts to hide.

What stands out:

• Up to 30 seconds per generation, with the option to extend further.
• Audio generated in the same pass.
• A very large reference budget: up to 30 images, 10 videos and 10 audio clips per request, according to ByteDance.
• Image-to-video with a first frame.

Where it is weaker: resolution. On Jantaris it tops out at 1080p (480p, 720p and 1080p are available). That is plenty for vertical social video viewed on a phone, less so for a 4K brand film.

The full parameter reference and Python code are in the Seedance 2.5 API guide.

Kling 3.0: best for scenes with several shots and dialogue

Kuaishou's Kling 3.0 was announced in early February 2026 and rolled out globally in March. It is built for short narrative sequences.

What stands out:

• Up to 15 seconds per generation.
• Several shots described in one prompt: Kling cuts between them in one generation and keeps characters consistent. The vendor's separate multi-shot mode, with its own prompt and length per shot, is not yet available on Jantaris.
• Optional native audio (generate_audio) with character-level lip-sync, and multiple speaking characters in one scene.
• 720p, 1080p and 4K output.

Where it is weaker: 15 seconds caps a single take, and prompts with several shots take more care to write. If you just want one clean shot, a simpler prompt on Seedance or Veo is often faster to get right.

I use Kling when a brief says "a short scene with two people talking" rather than "a beautiful shot of X".

Veo 3.1: best for high-resolution short clips

On Jantaris, Google's Veo 3.1 always generates a fixed 8-second clip at 720p, 1080p or 4K, and you pay per clip rather than per second (4K costs more than 720p and 1080p). Audio (dialogue, ambience, sound effects) is always generated and included in the price, there is no switch to turn it off.

What stands out:

• Some of the best light and material rendering in the group, with 4K on the main model.
• Up to three reference images to keep a subject consistent.
• A simple, predictable price: one clip, one rate.

Available only on Google's own API: 4 and 6 second clips, first and last frame control, and extensions (extending a clip in 7-second steps). None of these are exposed on Jantaris yet.

Where it is weaker: 8 seconds is short, and only two aspect ratios (16:9 and 9:16). Veo 3.1 is also the premium option of the group, so I save it for final renders rather than exploration.

Wan 3.0: 30 seconds up to 4K, the fourth model on the same key

Alibaba released Wan 3.0 on August 6, 2026, as the successor to Wan 2.7. It is the fourth model in this comparison you can call with the same Jantaris key, next to the stronger Wan 3.0 Video Prime. The older model in the family is Wan 2.7 Video (up to 15 s at 1080P).

What stands out:

• 2 to 30 seconds in one continuous generation.
• Resolutions 480P, 720P, 1080P, 2K and 4K, with the per-second rate set by resolution, so 480P drafts are very cheap.
• Audio on by default, with a switch to turn it off.
• References: up to 10 images, 5 video clips and 5 audio clips.
• It can build a video from one document (a slide deck, spreadsheet or PDF) or a public web page.

What to know: Wan 3.0 has no open weights. The last open-weight Wan video model is Wan 2.2 (Apache 2.0), which you can still run locally on your own GPU if self-hosting matters more than quality.

Head-to-head pages:

• Wan 3.0 vs Seedance 2.5
• Wan 3.0 vs Kling 3.0
• Wan 3.0 vs Wan 3.0 Prime

Which AI video API should you choose?

Here is how I decide:

The table is a starting point. Video models differ a lot by subject matter, so the only reliable test is your own prompts.

Test Seedance, Kling, Veo and Wan side by side

With one API and one key, an A/B test is a loop. This script sends the same prompt to four models, waits for all of them, and saves the files with the cost of each.

import os
import time
import requests

API = "https://jantaris.com/v1"
HEADERS = {"Authorization": f"Bearer {os.environ['AI_API_KEY']}"}

PROMPT = (
    "A barista pours latte art in a sunlit cafe, close-up, shallow depth of field, "
    "soft clinking of cups and quiet chatter"
)

JOBS = {
    "seedance-2.5": {"duration": 8, "resolution": "720p"},
    "kling-3.0": {"duration": 8},
    "veo-3.1": {"duration": 8, "resolution": "720p"},
    "wan-3.0": {"duration": 8, "resolution": "720P"},
}

tasks = {}
for model, extra in JOBS.items():
    body = {"model": model, "input": {"prompt": PROMPT, "aspect_ratio": "16:9", **extra}}
    r = requests.post(f"{API}/generate", headers=HEADERS, json=body, timeout=30)
    data = r.json()
    if r.status_code != 202:
        print(model, "rejected:", data["error"]["message"])
        continue
    tasks[model] = data["id"]
    print(model, "queued, estimated", data["estimated_cost"])

pending = dict(tasks)
while pending:
    time.sleep(10)
    for model, task_id in list(pending.items()):
        t = requests.get(f"{API}/tasks/{task_id}", headers=HEADERS, timeout=30).json()
        if t["status"] == "succeeded":
            url = t["output"][0]["url"]
            with open(f"{model}.mp4", "wb") as f:
                f.write(requests.get(url, timeout=120).content)
            print(model, "done, cost", t["cost"])
            del pending[model]
        elif t["status"] == "failed":
            print(model, "failed (not charged):", t["error"])
            del pending[model]

A few things this handles for you:

• Different parameters per model. Resolution options differ from model to model (Wan uses 720P in capitals), so I leave resolution out for Kling and let it use its default. Check each model's schema with GET /v1/models/{id} before you add fields.
• Rejections before cost. Invalid inputs return 422 with a message, nothing is charged.
• Failures are free. If one model's content filter blocks the prompt, that task ends as failed with cost 0.

For more than a handful of jobs, replace the polling loop with webhooks. I show the full setup in Building an AI video pipeline with async tasks and webhooks.

Pricing: how the four compare

On Jantaris, Seedance, Kling and Wan are billed per second of output and Veo 3.1 per 8-second clip. Higher resolution tiers cost more on all four, so the length and resolution you pick matter as much as the model.

The current starting rates (lowest resolution tier) are:

• Seedance 2.5: from $0.261 per second
• Kling 3.0: from $0.169 per second
• Veo 3.1 (Quality): from $2.53 per video
• Wan 3.0: from $0.0777 per second

The A/B script above costs 8 × from $0.261 per second + 8 × from $0.169 per second + 1 × from $2.53 per video (one clip) + 8 × from $0.0777 per second, as a floor: at 720p and above the real total is higher. Each request also returns estimated_cost for your exact parameters before it runs, and the AI cost calculator does the math for a whole batch. I break down real-world budgets (a 30-second reel, a batch of product clips) in How much does AI video cost per second?.

My workflow in practice

What works for me on client projects:

1. Explore with Seedance 2.5 at 480p, four variations per prompt.
2. Lock the look by generating a first frame with an image model (see Generate AI images with Python).
3. Render the final with the model that fits the format: Seedance for long vertical takes, Wan for long 4K clips on a budget, Kling for dialogue scenes, Veo for 4K hero shots.
4. Download immediately. Output links expire, so files go to my own storage the moment a task succeeds.

If you prefer clicking to coding, the same four models are in Studio on the same balance.

FAQ

Which AI video API generates the longest clips?

Seedance 2.5 and Wan 3.0 both generate up to 30 seconds in one pass. Kling 3.0 goes up to 15 seconds, and Veo 3.1 on Jantaris generates a fixed 8-second clip.

Which video model supports 4K?

On Jantaris, 4K is available on Veo 3.1 (8-second clip), Kling 3.0 (up to 15 s) and Wan 3.0 (up to 30 s). Seedance 2.5 tops out at 1080p.

Do these models generate sound?

Yes, all four generate audio natively. Veo 3.1 always generates audio, Kling 3.0 adds lip-synced dialogue, and on Seedance 2.5 and Wan 3.0 you can switch audio off with generate_audio: false.

Is there an open-source alternative to these APIs?

Wan 2.2 is the latest Wan video model with open weights (Apache 2.0) that you can run locally. Wan 3.0 and the others in this comparison are closed models available only through APIs.

Can I set Veo 3.1 to 4 or 6 seconds?

Not on Jantaris. Here Veo 3.1 always generates an 8-second clip and you pay per clip. 4 and 6 second clips, first and last frame control and extensions are available only on Google's own API.

Is Wan available through Jantaris?

Yes. The catalog has Wan 3.0, the stronger Wan 3.0 Video Prime and the older Wan 2.7 Video, all on the same key and balance.

Can I call Seedance, Kling, Veo and Wan with one API key?

Yes. On Jantaris all four use the same POST /v1/generate endpoint and one prepaid balance. You switch models by changing the model field.