Vidu MoE vs Q3 Pro vs Q3 Turbo: Which to Choose

If I had to sum it up in one line: use Vidu MoE for harder prompt logic, use Q3 Pro for final output, and use Q3 Turbo for lower-cost testing through one APIMart setup.

Here’s the short version you can act on right away:

• I can access Vidu MoE, Vidu Q3 Pro, and Vidu Q3 Turbo through APIMart with one API key and one main request flow.
• The core endpoint is POST https://api.apimart.ai/v1/videos/generations.
• Video jobs are async, so I get a task_id first, then I poll GET /v1/tasks/{task_id} until the job is completed.
• Vidu supports:
  • text-to-video
  • image-to-video
  • reference-based video
  • first-last frame transitions
• Q3 models add built-in audio like dialogue, sound effects, and music.
• Clips can run up to 16 seconds, with 540p, 720p, or 1080p output.
• APIMart pricing in the article lists:
  • Q3 Pro: about $0.12/sec at 720p
  • Q3 Turbo: about $0.048/sec at 720p
• APIMart keeps results for 72 hours, so I should download files soon after the task completes.

Key Takeaways

• On APIMart, the premium Vidu option is Vidu Q3 Mix (viduq3-mix), a reference-to-video model with premium quality, stronger smart transitions and clips as short as 1 second; APIMart's docs do not describe it as a Mixture of Experts model (docs).
• Vidu Q3 Pro (viduq3-pro) targets final cinematic output with 1080p and synchronized audio, while Vidu Q3 Turbo (viduq3-turbo) focuses on lower cost, lower latency, and fast iteration.
• On APIMart, Q3 Pro costs about $0.12/sec and Q3 Turbo about $0.048/sec at 720p, and Q3 models generate clips of up to 16 seconds at 540p, 720p, or 1080p.
• All three models share one APIMart key and the async POST https://api.apimart.ai/v1/videos/generations flow, returning a task_id to poll via GET /v1/tasks/{task_id}.
• Start drafts in Q3 Turbo and move final 1080p renders to Q3 Pro, keep clips at 5–10 seconds for motion fidelity, and download outputs within 72 hours, while APIMart still keeps the results.

Quick comparison

What stands out to me is how simple the switch is: in most cases, I just change the model field and keep the rest of the setup the same. That makes the article less about setup work and more about picking the right model for cost, wait time, and output quality.

Vidu Models Explained: MoE vs. Q-Series

Vidu's MoE model: what it is and when to use it

The MoE (Mixture of Experts) model sends different parts of a generation task to specialized experts for motion, scene consistency, and prompt control. It makes the most sense for multi-scene or longer prompts where consistency matters more than raw speed.

There’s a catch, though. MoE takes more compute and has slower turnaround than the Q-Series ^[7]. For simple prompts, it’s often more than you need.

Vidu Q-Series and Vidu Q3 Pro: performance for production use

If MoE is the specialist, Q-Series is the option built for production work. Vidu Q3 Pro is designed for polished cinematic output and storyboard-driven videos ^[7]. It supports 1080p video, clips up to 16 seconds, and audio-video generation with synchronized dialogue and sound effects ^[1][2][4]. Through the Vidu Q3 Pro API, 720p output costs $0.12 per second on APIMart ^[2].

Vidu Q3 Turbo leans more toward speed and lower cost, with faster scene switching ^[6][7]. Through the Vidu Q3 Turbo API, it starts at $0.032 per second at 540p and costs $0.048 per second at 720p.

Vidu Q4 Preview: image and reference input up to 4K

The newest model, Vidu Q4 Preview (viduq4-preview), works only from images: it animates a single first frame or builds a clip from 1–15 reference images plus up to three MP3 audio clips. It does not do text-to-video. Clips run 3–16 seconds at 540p up to 4K, and the Vidu Q4 API costs $0.0912 per second at 720p for APIMart Gold members (as of November 2026). If you need text-to-video or first-last frame transitions, stay with Q3 Pro or Q3 Turbo (docs).

How to choose between MoE and Q-Series for your workflow

This choice mostly comes down to prompt complexity, turnaround time, and budget. If your workflow depends on strict instruction-following and multi-scene logic, go with MoE. If you need polished output with audio-visual sync, Q3 Pro is the better fit. Alternatively, Kling V3 provides another high-fidelity option for cinematic AI video. If your main goal is fast iteration or lower cost per clip, Q3 Turbo is the practical pick.

The table below maps each model to the kind of work it handles best. For those comparing high-end options, Veo 3.1 offers cinematic text-to-video and image-to-video up to 4K.

Next, see how to select a model, authenticate, and send the request through APIMart.

How to Access Vidu Through APIMart

Account setup, authentication, and API key handling

After you pick a model, you can send jobs through APIMart with one API key. First, create an APIMart account and generate your key from the API key management page in the dashboard ^[2][3].

Send each request with a Bearer token in the Authorization header:

Authorization: Bearer YOUR_API_KEY

For storage, keep keys in environment variables or a secret manager like AWS Secrets Manager or GCP Secret Manager. It also helps to use separate keys for development, staging, and production. If a key gets exposed, rotate it right away. Do the same on a set schedule. And when you log requests, save only the task_id - never the token itself ^[5].

Finding Vidu models, pricing, and input schema in APIMart

Once you're signed in, check the catalog before you send anything. That's where you can confirm model names, supported inputs, and current pricing. In APIMart's catalog, Vidu models are listed under Video Generation. You can also find other high-performance models like MiniMax-Hailuo-02 in the same category. Use that page to compare input schema, resolution, and per-second cost across MoE, Q3 Pro, and Q3 Turbo ^[2][3].

The main fields to watch are:

• model
• prompt
• duration
• resolution
• aspect_ratio

For text-to-video jobs, use aspect_ratio. For image-based jobs, the system uses the source image's ratio instead ^[2]. Text prompts are limited to 2,000 characters ^[2][3].

Endpoints, request structure, and async job handling

After you choose the model, submit the generation request and track the async job with the returned task_id. Send a POST request to https://api.apimart.ai/v1/videos/generations, then poll job status with GET https://api.apimart.ai/v1/tasks/{task_id} ^[2][5].

Jobs move through these states:

• pending
• processing
• completed
• failed

APIMart doesn't send webhooks for Vidu jobs, so poll GET /v1/tasks/{task_id} until the status is completed or failed. Once the job is completed, download the file right away; the video URL is in data.result.videos[0].url[0]. From there, you can map the request fields to either a text-to-video flow or a reference-based flow.

Step-by-Step Integration for Text-to-Video and Reference-Based Video

Basic text-to-video flow with model selection

After you pick a model from the catalog, the text-to-video flow is pretty simple. Send your API key from the server side in the Authorization header as Bearer {your_api_key}.

Here’s a minimal payload for a text-to-video job with viduq3-pro:

{
  "model": "viduq3-pro",
  "prompt": "A red fox running through a snowy forest at dusk, cinematic slow motion",
  "duration": 8,
  "resolution": "720p",
  "aspect_ratio": "16:9",
  "audio": true
}

The submit response returns a task_id with the status submitted. After that, poll GET /v1/tasks/{task_id} with the returned task_id; the job moves through pending and processing until it reaches completed or failed ^[2]. If you want to switch to viduq3-turbo, you mostly just change the model field.

The async pattern stays the same across modes. What changes are the input fields.

Adding image or reference inputs and advanced controls

For image-to-video, pass one image URL in the image_urls array. Use 0 images for text-to-video, 1 for image-to-video, and 2 for first-last-frame mode ^[2]. In image-based modes, the output aspect ratio comes from the source image, so you can leave out aspect_ratio ^[2]. If you upload files directly instead of using URLs, keep each image in PNG, JPEG, or WebP format, under 50 MB, and keep the total HTTP body under 20 MB ^[9][8].

For reference-based generation on APIMart, use the same POST /v1/videos/generations endpoint with model set to viduq3 or viduq3-mix, pass 1–7 reference images in image_urls, and write a required prompt of up to 5,000 characters (docs). The subjects array and @subjectname syntax only exist on Vidu's own platform. If you're using first-last frame mode, keep both images close in aspect ratio, ideally within a 0.8 to 1.25 ratio, to reduce failures ^[8]. When faces or hands are involved, keep motion prompts subtle to cut down on distortion artifacts ^[5].

The table below shows the main parameters across both flows:

Set a fixed seed while testing if you want the same visual result across runs ^[2][9].

Tracking usage, cost, and production reliability

Once your request is working, the next job is keeping cost and reliability under control in production.

Log the task_id and timestamp for every request. That gives you a safe way to debug without storing sensitive credentials ^[5]. It also helps to track queue time and generation time separately, so you can tell the difference between platform delay and model latency.

For cost estimation, Vidu Q3 Pro at 720p costs about $0.12 per second on APIMart, and Q3 Turbo costs about $0.048 per second ^[3][11]. Set automated alerts at 50%, 80%, and 100% of your monthly budget cap so spending doesn’t get away from you ^[5].

Retries matter too. On 5xx errors, use exponential backoff: retry at 2 seconds, then 5 seconds, then 15 seconds before showing an error to the user ^[5]. Short-lived failures still happen, so retries should be part of any shipping build.

Model Selection Checklist and Key Takeaways

Use-case checklist for developers, creators, and product teams

Pick based on three things: prompt complexity, speed, and output quality. The table below turns the model comparison into a practical shipping choice.

Once you’ve picked a row, keep the same request schema from the integration section. In plain English: start ideas in Q3 Turbo, then move the final 1080p render to Q3 Pro. It’s a simple workflow, and it helps you move fast without spending more than you need to.

For clips where motion fidelity matters most, aim for 5–10 seconds instead of stretching to the 16-second maximum. Shorter clips often give you tighter motion and fewer headaches.

Key points to remember before shipping

MoE is the pick for complex, multi-scene logic. Q3 Pro gives you high-fidelity, cinematic 1080p output ^[3]. Q3 Turbo is the lower-cost option at $0.048/sec at 720p ^[3].

On APIMart, switching between these models is just a single model parameter change. Everything else in the request stays the same ^[3]. That means you can test one model, swap to another, and keep your integration work steady.

Use the same async flow each time:

• Submit the request
• Capture task_id
• Poll GET /v1/tasks/{task_id} until the status is completed

Also, download generated videos soon after they're ready. APIMart keeps results for 72 hours ^[3][11].

FAQs

Which Vidu model should I start with?

Start with the model that fits your needs for speed, audio, and visual control.

• viduq3-pro: best for audio-visual sync and shot segmentation
• viduq3-turbo: faster generation than the pro version
• viduq3 or viduq3-mix: reference-to-video with 1–7 images; viduq4-preview for image or reference input up to 4K

How do I track a video job after submitting it?

On APIMart, you track a Vidu job by polling.

Save the task_id from the submit response, then call GET /v1/tasks/{task_id} at a steady interval. APIMart doesn't send webhooks for Vidu jobs, so there's no callback_url to configure.

Once the status changes to completed, the response includes the video URL in data.result.videos[0].url[0]. If it changes to failed, check the error message before you retry.

What inputs and limits should I know before integrating?

Before you integrate the Vidu API, make sure your inputs stay within these limits:

• Images: PNG, JPEG, JPG, or WebP only; each file must be under 50 MB and at least 128×128 pixels
• Total HTTP request body: 20 MB max
• Text prompts: up to 2,000 characters for Q3 Pro and Q3 Turbo, and up to 5,000 characters for Q3 and Q3 Mix

Duration limits depend on the model you use. Q3 Pro, Q3 Turbo and Q3 Mix support 1–16 seconds, while Q3 and Q4 Preview support 3–16 seconds.

Also, keep your API keys secure. Don’t expose them in client-side code. Send requests through a server-side intermediary instead.