One API for All AI Video Models — GenRelay vs Building It Yourself
You ship a SaaS product that generates video clips. You start with Veo 3.1 for cinematic output. A month later, a client needs shorter social clips at a lower cost per second — so you add Grok Imagine 1.0. Three months after that, per-generation billing from Omni Flash makes more sense for another tier.
Each new model is another auth flow, another request schema, another async polling loop to maintain. The question isn't whether a unified video API is more convenient — it's whether the trade-offs are worth it.
This article compares integrating video models through GenRelay's single endpoint against building and maintaining direct per-provider integrations.
What does "one API for all AI video models" actually mean?
A unified video API is a single authenticated endpoint that routes requests to different underlying video generation models. You send the same request structure regardless of model — the model field selects the provider. The response structure, polling mechanism, and auth header are identical across all models.
GenRelay implements this pattern. As of August 2026, the /v1/videos/generations endpoint exposes four video models: Veo 3.1 Lite, Grok Imagine 1.0, Grok Imagine 1.5, and Gemini Omni Flash. One API key authenticates all four.
Which video models does GenRelay expose under one endpoint?
| Model | Capability | Billing model | Price |
|---|---|---|---|
| Veo 3.1 Lite | Text-to-video, image-to-video, reference-to-video | Per second × resolution | 720p $0.060/s · 1080p $0.120/s · 4K $0.180/s |
| Grok Imagine 1.5 | Image-to-video | Per second | $0.022/s |
| Grok Imagine 1.0 | Text-to-video | Per second | $0.010/s |
| Gemini Omni Flash | Text-to-video | Per generation | 720p $0.10/gen · 1080p $0.15/gen |
The two billing models matter for workload math. Per-second billing (Veo 3.1, Grok) scales linearly with clip duration — a 15s clip costs 3× a 5s clip. Per-generation billing (Omni Flash) is fixed per job regardless of length, which makes it cost-effective for longer clips at lower resolution.
For a full cost comparison across clip lengths, see the AI video API cost breakdown and the Veo 3.1 API tutorial for model-specific parameters.
How do I call multiple video models from one endpoint?
The same function body works for all four models. Only the model field changes:
import requests
import time
GENRELAY_API_KEY = "your_key_here"
def generate_video(prompt: str, model: str = "veo-3.1-lite", duration: int = 8, resolution: str = "720p") -> str:
# Submit job
r = requests.post(
"https://genrelay.ai/v1/videos/generations",
headers={"Authorization": f"Bearer {GENRELAY_API_KEY}"},
json={
"model": model,
"prompt": prompt,
"duration": duration,
"resolution": resolution
}
)
r.raise_for_status()
job_id = r.json()["id"]
# Poll for completion — same endpoint and status schema for all models
while True:
status_r = requests.get(
f"https://genrelay.ai/v1/videos/generations/{job_id}",
headers={"Authorization": f"Bearer {GENRELAY_API_KEY}"}
)
status_r.raise_for_status()
status = status_r.json()
if status["status"] == "completed":
return status["output"]["url"]
elif status["status"] == "failed":
raise RuntimeError(f"Job failed: {status.get('error', 'unknown error')}")
time.sleep(5)
# Switch models by changing one field — polling logic, auth, and base URL stay identical
clip_cinematic = generate_video("Aerial view of a coastal city at golden hour", model="veo-3.1-lite")
clip_social = generate_video("Aerial view of a coastal city at golden hour", model="grok-1.0")
clip_flash = generate_video("Aerial view of a coastal city at golden hour", model="omni-flash")
If you integrated each provider directly, each generate_* function would use a different base URL, different request schema, different job status field names, and different polling error codes.
How does building direct provider integrations compare?
Direct integration with each video provider involves:
- Separate auth setup per provider — API keys, service accounts, or OAuth tokens; each provider's documentation covers a different flow
- Different request schemas — Veo 3.1's job submission parameters differ from Grok's and from Omni Flash's
- Different async polling — status field names, terminal states, and recommended polling intervals vary per provider
- Separate error code handling — rate limit codes, quota errors, and generation failures use different formats
- Independent update cycle — when a provider updates their API, only that integration breaks, but you still need to find it, read the changelog, and patch it separately
| Dimension | Direct per-provider integration | GenRelay unified endpoint |
|---|---|---|
| Auth | Separate credentials per provider | One Bearer token |
| Request schema | Provider-specific per model | Uniform (model field selects provider) |
| Async polling | Provider-specific | Same endpoint and schema for all models |
| Adding a new model | New integration from scratch | Update model string; check new parameters |
| Provider API changes | Each integration breaks independently | GenRelay absorbs schema changes |
| Initial build time (estimated) | 7–14 hours per provider | 7–14 hours total for all models |
The "initial build time" comparison is where the practical difference is largest. For four providers, direct integration requires 28–56 hours of initial engineering. A unified API endpoint means that same effort applies across all four models in the catalog.
How do I switch video models at runtime without changing application code?
Define a model routing map and select by use case. This keeps the business logic — which model fits which use case — decoupled from the API call itself:
VIDEO_MODEL_MAP = {
"cinematic": {"model": "veo-3.1-lite", "resolution": "1080p"},
"social_short": {"model": "grok-1.0", "resolution": "720p"},
"image_to_video":{"model": "grok-1.5", "resolution": "720p"},
"fast_preview": {"model": "omni-flash", "resolution": "720p"},
}
def create_video_for_use_case(prompt: str, use_case: str, duration: int = 8) -> str:
config = VIDEO_MODEL_MAP.get(use_case, VIDEO_MODEL_MAP["social_short"])
return generate_video(
prompt=prompt,
model=config["model"],
duration=duration,
resolution=config["resolution"]
)
# Business logic controls the model; API call is unchanged
clip = create_video_for_use_case("Product launch reveal animation", use_case="cinematic")
preview = create_video_for_use_case("Product launch reveal animation", use_case="fast_preview")
When GenRelay adds a new model to its catalog, you add one entry to VIDEO_MODEL_MAP. No new auth, no new polling loop, no new base URL.
For image-to-video jobs with Grok 1.5 or Veo 3.1 Lite, add an "image" field to the request body containing a URL to the source image. See the Grok video API guide for i2v-specific parameters, and the Veo model page for Veo 3.1 Lite duration and resolution limits.
What does a 10-second clip cost across all available models?
At 10 seconds and 720p:
| Model | Billing | Cost for 10s @ 720p |
|---|---|---|
| Veo 3.1 Lite | $0.060/s | $0.60 |
| Grok Imagine 1.5 (i2v) | $0.022/s | $0.22 |
| Grok Imagine 1.0 (t2v) | $0.010/s | $0.10 |
| Gemini Omni Flash | $0.10/gen | $0.10 (flat) |
Grok 1.0 and Omni Flash are cost-equivalent at 720p for 10s clips, but Omni Flash stays flat at $0.10 for longer clips — at 30 seconds, Omni Flash costs $0.10 while Grok 1.0 costs $0.30. The right model depends on your clip length distribution.
FAQ
Does GenRelay support audio in Veo 3.1 video generation?
Yes. As of August 2026, Veo 3.1 Lite via GenRelay supports audio generation. Add "audio": true to the request body on text-to-video requests. The Veo 3.1 API tutorial covers this parameter in detail.
Does GenRelay auto-fallback to another model if one provider is down?
No. If a job fails, GenRelay returns the provider error in the job status response. Fallback routing is your application's responsibility — check status["status"] == "failed" and retry with an alternate model value. Auto-fallback across models is not implemented at the routing layer because switching models changes output style, which is a product decision, not an infrastructure one.
Can I use the same API key for both image and video generation?
Yes. The same GenRelay API key authenticates requests to /v1/images/generations and /v1/videos/generations. Usage across both endpoints is tracked under a single account.
What are the rate limits on video job submission?
GenRelay enforces per-minute submission caps that vary by plan. Video jobs are long-running — the rate limit applies to new job submissions, not to active jobs completing. On a 429 response, implement exponential backoff starting at 10 seconds; the Retry-After header in the response gives the minimum wait time.
Is there a free tier for video generation?
GenRelay's free tier includes credits that apply across all models, including video. Video generation consumes credits at a higher rate per request than image generation given the higher compute cost. Current credit allocations are listed on the GenRelay pricing page.