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Vidu Q1 Reference Image-to-Video

Create short generative video with Vidu Q1 Reference Image-to-Video on LLM.API, with resolution-aware pricing and a unified developer workflow.

Start Using API

What is Vidu Q1 Reference Image-to-Video?

Vidu Q1 Reference Image-to-Video targets motion content rather than chat. Video generation model by Muapi. On LLM.API it sits alongside other media models under a single developer account.

Providers

LLM.API routes Vidu Q1 Reference Image-to-Video to the providers below, with discounted effective rates versus list price.

List price by provider ($ / 1M tokens)

InputOutput
muapi$0 in
$0 out

Provider list prices; the LLM.API discount applies on top.

ProviderPricingContextCapabilities
muapi30% offin —; out $0.08 per second of video——

Prices and availability from the LLMAPI catalogue, updated nightly. Last updated 21 Sept 2026.

Try this model

Test Vidu Q1 Reference Image-to-Video right here — free to start.

Vidu Q1 Reference Image-to-Video
Hi! Want to test the model?

Suggestions for your first prompt

Code snippet

Call Vidu Q1 Reference Image-to-Video through the OpenAI-compatible API — Video generation via LLM.API (see docs for media endpoints).

python
from openai import OpenAI

client = OpenAI(
    api_key="YOUR_LLMAP_KEY",
    base_url="https://api.llmapi.ai/v1",
)

resp = client.chat.completions.create(
    model="vidu-q1-reference",
    messages=[
        {"role": "system", "content": "You are a precise product assistant."},
        {"role": "user", "content": "Give me three crisp launch checklist items."},
    ],
)
print(resp.choices[0].message.content)
{
  "model": "vidu-q1-reference",
  "messages": [
    {"role": "system", "content": "You are a precise product assistant."},
    {"role": "user", "content": "Give me three crisp launch checklist items."}
  ]
}

5 Core Capabilities

  • Motion coherence

    Targets temporally consistent motion across frames for the requested scene.

  • Short-form content

    Fits vertical and horizontal short-form marketing formats. Grounded in the model's video role rather than generic chat claims.

  • Product visualization

    Helps visualize products and environments before shoot or 3D work. Reflects video generation positioning for this endpoint.

  • Cinematic prompting

    Responds to camera, lighting, and mood language in creative briefs.

  • Text-to-video generation

    Synthesizes short video clips from prompts for ads, explainers, and social. Tuned to how teams typically call Vidu Q1 Reference Image-to-Video.

6 Most Valuable Use Cases

  • UGC-style drafts for performance marketing with Vidu Q1 Reference Image-to-Video
  • Localized motion variants of the same concept
  • Short promotional clips from written briefs with Vidu Q1 Reference Image-to-Video
  • Creative exploration for campaign storyboards
  • Social-first product teaser generation with Vidu Q1 Reference Image-to-Video
  • Explainer openers before live-action shoots

Why Build on LLM.API?

One unified API. Every major model. Built-in reliability, cost control, and observability.

  • Intelligent AI Routing

    Automatically route each request to the best model across providers based on latency, cost, and quality—without changing your integration or redeploying code.

    One endpoint, every model.

  • Cost-Aware Execution

    Control spend with per-request cost estimation, smart model selection, and centralized quotas so teams can experiment fast without runaway bills or manual tracking.

    More performance, less spend.

  • Resilient Fallback Flows

    Define automatic, provider-agnostic fallbacks to keep your app up during outages, rate limits, or timeouts—no brittle failover logic scattered through your codebase.

    Never go dark on users.

  • Deep LLM Observability

    Trace every call across providers with logs, metrics, and request replay so you can debug, tune prompts, and optimize model choices from one unified dashboard.

    See every token, everywhere.

  • Task-Level Orchestration

    Describe tasks, not models. LLM.API maps them to the right tools, models, and prompts so you ship complex AI workflows with minimal glue code.

    Think tasks, not models.

  • High-Throughput Batch APIs

    Process millions of inferences efficiently with optimized batch pipelines, concurrency controls, and retry logic—all behind the same simple interface you use for single calls.

    Scale from 1 to millions.

Why run Vidu Q1 Reference Image-to-Video on LLM.API?

  • Unified AI Routing

    Practical: Reach Vidu Q1 Reference Image-to-Video and sibling models through one OpenAI-compatible endpoint.

  • Cost Control

    Compare provider price points and keep spend visible as you scale Vidu Q1 Reference Image-to-Video.

  • Reliability Layer

    Retry and route across configured providers when a single upstream blips.

  • Observability

    Practical: Trace prompts, tokens, and errors for Vidu Q1 Reference Image-to-Video alongside the rest of your stack.

  • Drop-in SDKs

    Production: Keep using familiar OpenAI client patterns with base URL https://api.llmapi.ai/v1.

  • Model Breadth

    Practical: Swap Vidu Q1 Reference Image-to-Video for chat, media, or embedding alternatives without rewriting auth.

When to Use — When NOT to Use

Use it if...

  • You can tolerate longer generation times than chat (Vidu Q1 Reference Image-to-Video)
  • You are building short-form generative video features (Vidu Q1 Reference Image-to-Video)
  • You need resolution-tiered pricing for motion content (Vidu Q1 Reference Image-to-Video)

Avoid if...

  • You need broadcast-length films or guaranteed cinema-grade continuity
  • You require sub-second interactive generation
  • You only need still images or chat text

COMMUNITY

What creators say about AI video models

Summarised from publicly published developer and community reviews of this model family. Opinions are the sources’, not LLM.API’s, and may not be specific to Vidu Q1 Reference Image-to-Video.

  • Creator reviews of the latest Kling releases praise multi-shot consistency, native audio and genuine 4K output.
  • Comparisons with Sora and Runway focus on prompt adherence and motion stability rather than raw resolution.
  • The common workflow advice: generate many short takes cheaply, then upscale or extend the ones that land.

SOURCES

Frequently Asked Questions

  • How long do Vidu Q1 Reference Image-to-Video jobs take?

    Video generation typically takes longer than chat; latency scales with duration and resolution and may vary by queue.

  • How do I call Vidu Q1 Reference Image-to-Video via API?

    Send OpenAI-compatible requests to https://api.llmapi.ai/v1 with model "vidu-q1-reference" and your LLM.API key. See the code snippet on this page.

  • What is Vidu Q1 Reference Image-to-Video?

    Video generation model by Muapi. On LLM.API it is addressed as `vidu-q1-reference`.

  • What modalities does Vidu Q1 Reference Image-to-Video support?

    Vidu Q1 Reference Image-to-Video accepts text, image and produces video according to its architecture metadata on LLM.API.

  • Is Vidu Q1 Reference Image-to-Video a chat model?

    No—Vidu Q1 Reference Image-to-Video is categorized as a video model. Use the matching API surface rather than assuming chat completions.

  • Which providers serve Vidu Q1 Reference Image-to-Video?

    LLM.API currently lists: muapi. Availability can vary by region and account.

  • Does Vidu Q1 Reference Image-to-Video support streaming?

    Streaming depends on the active provider; check the providers table on this page for flags.

  • How is Vidu Q1 Reference Image-to-Video priced on LLM.API?

    Listed pricing metadata shows: $0.08/sec. Confirm live rates in the LLM.API dashboard or docs before production budgeting.

  • What are limitations of Vidu Q1 Reference Image-to-Video?

    Like other API models, Vidu Q1 Reference Image-to-Video can be wrong, incomplete, or uneven on edge cases. Validate outputs for high-stakes use. Media/OCR/STT models additionally depend on input quality.

  • What is the context length for Vidu Q1 Reference Image-to-Video?

    Reported context for Vidu Q1 Reference Image-to-Video is See provider specs. Always verify the active provider row if multiple providers are listed.

  • When should I choose Vidu Q1 Reference Image-to-Video?

    You are building short-form generative video features — especially when you specifically need Vidu Q1 Reference Image-to-Video.

  • Where is the canonical page for Vidu Q1 Reference Image-to-Video?

    https://llmapi.ai/models/vidu-q1-reference/

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