Seedance, Kling or Veo for your API workload

Updated 2026-10-02

Developers asking "Seedance or Kling or Veo?" usually want a pick, but the useful answer is a method. Quality claims age badly and depend on your prompts, so this page does not rank outputs. It covers what you can verify: which input modes each family exposes, how variants and hosts differ, and how to make the choice cheap to revisit.

Step 1: list the input modes your product needs

Write down the modes first. VideoRouter's POST /videos has four: text-to-video, image-to-video (start_image_url), reference-to-video (input_references, input_video_references, input_audio_references) and editing (input_video_url). Support varies per model and per host, not per brand. Examples VideoRouter's documentation shows:

• Seedance has documented multi-modal reference-to-video (up to 9 images, 3 videos, 3 audio) on specific Fal-hosted 2.0 endpoints, and a ladder of Full, Fast and Mini variants.
• Kling has several lines in the catalog (v2.6, v3, v3 Omni, v3 Turbo, motion control). The Omni line supports an editing mode through input_video_url on one documented host, and motion control is its own model with its own input rules.
• Veo 3.1 comes as Full, Fast and Lite rows. Check each model page for modes; do not assume the three rows are identical.

Kling 4.0 was announced on 2026-09-28 but is not available on any host in the catalog yet; plan around what is listed.

Step 2: map workload to tier structure

Step 3: look at host breadth, not just the model

The same checkpoint is sold by several providers at different prices and with different reliability. Some families are sold by many hosts and others by few, which changes both your price spread and your failover options. A model with one host is a single point of failure for your feature no matter how good it is. The table is regenerated from the live catalog, so check it instead of trusting a number from an article:

Per second, before VideoRouter's 2% platform fee. For tiered models each row compares the resolution tier with the widest host-to-host gap. Built 2026-10-02 from the live catalog.

Where each workload tends to go wrong

Most failed evaluations are workload mismatches rather than model failures. A team that needs character consistency picks a model on a text-to-video demo and finds out late that the host serving it takes one reference image at most. A team that needs high throughput picks the single best row and discovers the host's rate limit at launch. A team that needs editing assumes the family they chose supports it. Write the mode, volume and fallback requirements down before you open a single model page, then use the pages to confirm them.

Step 4: pin or float

An unpinned request is routed to the cheapest healthy host, with automatic failover when a host is down or rate-limited. A pinned request (model/host, for example bytedance/seedance-2.0/fal) stays on that host. Float for text-to-video and simple image-to-video where hosts are interchangeable. Pin when a host has capabilities others lack (for example reference arrays) or when you have a contractual or data-handling reason to choose one.

Step 5: make the decision reversible

Because every family goes through the same endpoint, a comparison is a loop over model ids with one prompt set:

MODELS = ["bytedance/seedance-2.5", "kling-v3.0-std", "google/veo-3.1-fast"]

for m in MODELS:
    job = requests.post("https://videorouter.sh/api/v1/videos", headers=H, json={
        "model": m,
        "prompt": PROMPT,
        "duration_secs": 5,
        "aspect_ratio": "16:9",
    }).json()
    print(m, job["id"])

Notes for running it honestly: the same prompt can produce different results per model, so score on your own prompts and criteria; durations are snapped to what each model supports and billing follows the requested, snapped length; errors come back OpenAI-style as {error:{message,type,code}} so one handler covers all three; and the platform fee is 2% on image and video, with polling free and failed upstream jobs not billed.

A simple decision order

1. Eliminate models that lack a mode you need.
2. Among the rest, prefer those with several hosts if the feature is customer-facing.
3. Run your own 10-20 prompt set on the finalists at the same duration and resolution; keep the outputs.
4. Pick on your criteria, then decide the draft variant for iteration and the final variant for delivery.
5. Keep the second-place model in config as a fallback you can switch to by changing a string.

The pricing page lists Seedance rows, the models page links each row's host table, and the quickstart has the request. Create a key to run the loop above.

Frequently asked questions

Keep reading

• Seedance 2.5 vs 2.0 vs Fast vs Mini — Choosing a Variant for API Use
• Seedance Reference-to-Video API: Images, Video, Audio Refs
• Seedance Image-to-Video API: start_image_url Prompts & Setup
• How to Call the Seedance 2.5 API: curl and Python Examples