Veo3.1 Image-to-Video
Veo3.1 Image-to-Video exposes video generation video generation through LLM.API so motion experiments share the same billing and auth as other models.
What is Veo3.1 Image-to-Video?
Veo3.1 Image-to-Video is a generative video model available through LLM.API as `veo3.1-reference-to-video`. Video generation model by Muapi. Expect text, image prompts and video outputs, with pricing often tied to seconds and resolution.
Providers
LLM.API routes Veo3.1 Image-to-Video to the providers below, with discounted effective rates versus list price.
List price by provider ($ / 1M tokens)
InputOutputProvider list prices; the LLM.API discount applies on top.
| Provider | Pricing | Context | Capabilities |
|---|---|---|---|
| muapi30% off | in —; out $0.406 per second of video | — | — |
Prices and availability from the LLMAPI catalogue, updated nightly. Last updated 21 Sept 2026.
Try this model
Test Veo3.1 Image-to-Video right here — free to start.
Suggestions for your first prompt
Code snippet
Call Veo3.1 Image-to-Video through the OpenAI-compatible API — Video generation via LLM.API (see docs for media endpoints).
from openai import OpenAI
client = OpenAI(
api_key="YOUR_LLMAP_KEY",
base_url="https://api.llmapi.ai/v1",
)
resp = client.chat.completions.create(
model="veo3.1-reference-to-video",
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": "veo3.1-reference-to-video",
"messages": [
{"role": "system", "content": "You are a precise product assistant."},
{"role": "user", "content": "Give me three crisp launch checklist items."}
]
}5 Core Capabilities
Storyboard acceleration
Turns written beats into moving drafts for rapid review. Relevant for `veo3.1-reference-to-video` workloads on LLM.API.
Iterative creatives
Enables prompt-based A/B exploration of motion concepts. Grounded in the model's video role rather than generic chat claims.
Short-form content
Fits vertical and horizontal short-form marketing formats. Grounded in the model's video role rather than generic chat claims.
Cinematic prompting
Responds to camera, lighting, and mood language in creative briefs. Relevant for `veo3.1-reference-to-video` workloads on LLM.API.
Resolution options
Supports multiple output resolutions depending on provider pricing tiers. Tuned to how teams typically call Veo3.1 Image-to-Video.
6 Most Valuable Use Cases
- Explainer openers before live-action shoots with Veo3.1 Image-to-Video
- Short promotional clips from written briefs
- Internal pitch videos for stakeholders with Veo3.1 Image-to-Video
- Localized motion variants of the same concept
- Social-first product teaser generation with Veo3.1 Image-to-Video
- Creative exploration for campaign storyboards
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 Veo3.1 Image-to-Video on LLM.API?
Unified AI Routing
Practical: Reach Veo3.1 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 Veo3.1 Image-to-Video.
Reliability Layer
Retry and route across configured providers when a single upstream blips.
Observability
Trace prompts, tokens, and errors for Veo3.1 Image-to-Video alongside the rest of your stack.
Drop-in SDKs
Practical: Keep using familiar OpenAI client patterns with base URL https://api.llmapi.ai/v1.
Model Breadth
Swap Veo3.1 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 (Veo3.1 Image-to-Video)
- You are building short-form generative video features (Veo3.1 Image-to-Video)
- You can tolerate longer generation times than chat (Veo3.1 Image-to-Video)
Avoid if...
- You only need still images or chat text
- You require sub-second interactive generation
- 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 Veo3.1 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
Is Veo3.1 Image-to-Video a chat model?
No—Veo3.1 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 Veo3.1 Image-to-Video?
Reported context for Veo3.1 Image-to-Video is See provider specs. Always verify the active provider row if multiple providers are listed.
Which providers serve Veo3.1 Image-to-Video?
LLM.API currently lists: muapi. Availability can vary by region and account.
Does Veo3.1 Image-to-Video support streaming?
Streaming depends on the active provider; check the providers table on this page for flags.
What modalities does Veo3.1 Image-to-Video support?
Veo3.1 Image-to-Video accepts text, image and produces video according to its architecture metadata on LLM.API.
Can I use tools or structured outputs with Veo3.1 Image-to-Video?
Tooling support varies; for pure video models, prefer the modalities listed rather than assuming chat tools.
How do I call Veo3.1 Image-to-Video via API?
Send OpenAI-compatible requests to https://api.llmapi.ai/v1 with model "veo3.1-reference-to-video" and your LLM.API key. See the code snippet on this page.
What are limitations of Veo3.1 Image-to-Video?
Like other API models, Veo3.1 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 Veo3.1 Image-to-Video?
Video generation model by Muapi. On LLM.API it is addressed as `veo3.1-reference-to-video`.
When should I choose Veo3.1 Image-to-Video?
You need resolution-tiered pricing for motion content — especially when you specifically need Veo3.1 Image-to-Video.
Where is the canonical page for Veo3.1 Image-to-Video?
https://llmapi.ai/models/openai-veo3-1-reference-to-video/
COMPARE
Competitive Models
Kling V2.1 Standard Image-to-Video
Another video option from the video generation lineup on LLM.API.
Wan2.1 Image-to-Video
Consider Wan2.1 Image-to-Video when you want a related video alternative to Veo3.1 Image-to-Video.
HappyHorse 1.1 Text-to-Video
Sibling-style choice: HappyHorse 1.1 Text-to-Video (happyhorse-1.1-t2v) for comparable video workloads.
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