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Vidu Q2 Reference Image-to-Video

Create short generative video with Vidu Q2 Reference Image-to-Video on LLM.API, with resolution-aware pricing and a unified developer workflow.

Start Using API

What is Vidu Q2 Reference Image-to-Video?

Vidu Q2 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 Q2 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 $0.064 per second of video——

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

Try this model

Test Vidu Q2 Reference Image-to-Video right here — free to start.

Vidu Q2 Reference Image-to-Video
Hi! Want to test the model?

Suggestions for your first prompt

Code snippet

Call Vidu Q2 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-q2-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-q2-reference",
  "messages": [
    {"role": "system", "content": "You are a precise product assistant."},
    {"role": "user", "content": "Give me three crisp launch checklist items."}
  ]
}

5 Core Capabilities

  • Cinematic prompting

    Responds to camera, lighting, and mood language in creative briefs. Tuned to how teams typically call Vidu Q2 Reference Image-to-Video.

  • Short-form content

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

  • Storyboard acceleration

    Turns written beats into moving drafts for rapid review.

  • Product visualization

    Helps visualize products and environments before shoot or 3D work. Grounded in the model's video role rather than generic chat claims.

  • Text-to-video generation

    Synthesizes short video clips from prompts for ads, explainers, and social.

6 Most Valuable Use Cases

  • Creative exploration for campaign storyboards with Vidu Q2 Reference Image-to-Video
  • Internal pitch videos for stakeholders
  • Localized motion variants of the same concept with Vidu Q2 Reference Image-to-Video
  • Short promotional clips from written briefs
  • Explainer openers before live-action shoots with Vidu Q2 Reference Image-to-Video
  • Social-first product teaser generation

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 Q2 Reference Image-to-Video on LLM.API?

  • Unified AI Routing

    Practical: Reach Vidu Q2 Reference Image-to-Video and sibling models through one OpenAI-compatible endpoint.

  • Cost Control

    Production: Compare provider price points and keep spend visible as you scale Vidu Q2 Reference Image-to-Video.

  • Reliability Layer

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

  • Observability

    Practical: Trace prompts, tokens, and errors for Vidu Q2 Reference Image-to-Video alongside the rest of your stack.

  • Drop-in SDKs

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

  • Model Breadth

    Swap Vidu Q2 Reference Image-to-Video for chat, media, or embedding alternatives without rewriting auth.

When to Use — When NOT to Use

Use it if...

  • You need resolution-tiered pricing for motion content (Vidu Q2 Reference Image-to-Video)
  • You are building short-form generative video features (Vidu Q2 Reference Image-to-Video)
  • You can tolerate longer generation times than chat (Vidu Q2 Reference Image-to-Video)

Avoid if...

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

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 Q2 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

  • What modalities does Vidu Q2 Reference Image-to-Video support?

    Vidu Q2 Reference Image-to-Video accepts text, image and produces video according to its architecture metadata on LLM.API.

  • Where is the canonical page for Vidu Q2 Reference Image-to-Video?

    https://llmapi.ai/models/vidu-q2-reference/

  • Which providers serve Vidu Q2 Reference Image-to-Video?

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

  • When should I choose Vidu Q2 Reference Image-to-Video?

    You can tolerate longer generation times than chat — especially when you specifically need Vidu Q2 Reference Image-to-Video.

  • Is Vidu Q2 Reference Image-to-Video a chat model?

    No—Vidu Q2 Reference Image-to-Video is categorized as a video model. Use the matching API surface rather than assuming chat completions.

  • What is the context length for Vidu Q2 Reference Image-to-Video?

    Reported context for Vidu Q2 Reference Image-to-Video is See provider specs. Always verify the active provider row if multiple providers are listed.

  • Does Vidu Q2 Reference Image-to-Video support streaming?

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

  • Can I use tools or structured outputs with Vidu Q2 Reference Image-to-Video?

    Tooling support varies; for pure video models, prefer the modalities listed rather than assuming chat tools.

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