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.

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/

Which endpoint do I call for Veo3.1 Image-to-Video?

POST https://api.llmapi.ai/v1/chat/completions with model "veo3.1-reference-to-video" and your LLM.API key. The request and response bodies are OpenAI-compatible.

How do I switch from OpenAI to Veo3.1 Image-to-Video on LLM.API?

Change two lines: set base_url to https://api.llmapi.ai/v1 and api_key to your LLM.API key. The rest of your OpenAI SDK code stays the same.

Does Veo3.1 Image-to-Video support function calling and structured outputs?

Function calling: not supported. Structured outputs: not supported.

Veo3.1 Image-to-Video API: Endpoint & Pricing

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.

Start Using API

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.

Can you self-host Veo3.1 Image-to-Video?

No. We found no public weights for Veo3.1 Image-to-Video on Hugging Face, so there is nothing to download, quantize or serve on your own GPUs: no VRAM budget, no vLLM or GGUF build to plan for. The only way to run it is over an API.

Skip the deploy — use LLM.API as your endpoint

No GPUs, no quantization trade-offs. Same model, OpenAI-compatible, with custom volume discounts on request.

Get API key See API code ↓

Providers

LLM.API routes Veo3.1 Image-to-Video to the providers below, with discounted effective rates versus list price.

List price by provider

InputOutput

muapi$0 in

$0.0004 out

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

Provider	Pricing	Context	Capabilities
muapi	in —; out $0.0004 per second of video	—	—

Prices and availability from the LLMAPI catalogue, updated nightly. Last updated 11 Oct 2026.

Try this model

Test Veo3.1 Image-to-Video right here — free to start.

Veo3.1 Image-to-Video

Hi! Want to test the model?

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).

Switching from OpenAI? Change 2 lines.

- base_url="https://api.openai.com/v1"
- api_key="YOUR_OPENAI_KEY"
+ base_url="https://api.llmapi.ai/v1"
+ api_key="YOUR_LLMAPI_KEY"

Everything else stays the same — SDK, message format, tools, streaming. Set model to veo3.1-reference-to-video and the call runs unchanged.

bash

curl https://api.llmapi.ai/v1/chat/completions \
  -H "Authorization: Bearer $LLMAPI_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "veo3.1-reference-to-video",
    "messages": [
      {"role": "user", "content": "Give me three crisp launch checklist items."}
    ]
  }'

from openai import OpenAI

client = OpenAI(
    api_key="YOUR_LLMAPI_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)

import OpenAI from "openai";

const client = new OpenAI({
  apiKey: process.env.LLMAPI_KEY,
  baseURL: "https://api.llmapi.ai/v1",
});

const resp = await client.chat.completions.create({
  model: "veo3.1-reference-to-video",
  messages: [
    { role: "user", content: "Give me three crisp launch checklist items." },
  ],
});

console.log(resp.choices[0].message.content);

stream = client.chat.completions.create(
    model="veo3.1-reference-to-video",
    messages=[{"role": "user", "content": "Write a haiku about latency."}],
    stream=True,
)

for chunk in stream:
    delta = chunk.choices[0].delta.content
    if delta:
        print(delta, end="", flush=True)

{
  "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."}
  ]
}

ENDPOINTS

Supported endpoints & features

Base URL https://api.llmapi.ai/v1 · model ID veo3.1-reference-to-video · OpenAI-compatible.

POST /v1/chat/completionsChat Completions — supported

Feature	Status	How to set it
Function calling (tools)	Not supported	`tools, tool_choice`
Parallel tool calls	Not supported	`parallel_tool_calls`
JSON mode	Not supported	`response_format: {"type": "json_object"}`
Structured outputs	Not supported	`response_format: {"type": "json_schema", …}`
Streaming	Not supported	`stream: true`
Vision (image input)	Not supported	`image_url content parts`
Web search	Not supported	`web_search`

ERRORS

Errors & fallback routing

Code	What it means	What to do
`401`	Missing or invalid API key.	Send `Authorization: Bearer YOUR_LLMAPI_KEY` and check the key is active.
`429`	Rate limited, or the upstream provider is throttling the request.	Back off and retry with jitter; the gateway also retries the request on another provider where one is available.
`5xx`	Upstream provider error or timeout.	Retry; fallback routing sends the retry to the next healthy provider for this model.

When a provider fails or throttles, the request is routed to the next provider serving this model — the ones listed in the providers table above.

Veo3.1 Image-to-Video in production

Best workloadsLLM.API features

What the model is good at.

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.

What you get when you call Veo3.1 Image-to-Video through LLM.API.

Unified AI Routing
Practical: Reach Veo3.1 Image-to-Video and sibling models through one OpenAI-compatible endpoint.
One endpoint, every model.
Cost Control
Production: Compare provider price points and keep spend visible as you scale Veo3.1 Image-to-Video.
More performance, less spend.
Reliability Layer
Retry and route across configured providers when a single upstream blips.
Never go dark on users.
Observability
Trace prompts, tokens, and errors for Veo3.1 Image-to-Video alongside the rest of your stack.
See every token, everywhere.
Drop-in SDKs
Practical: Keep using familiar OpenAI client patterns with base URL https://api.llmapi.ai/v1.
Think tasks, not models.
Model Breadth
Swap Veo3.1 Image-to-Video for chat, media, or embedding alternatives without rewriting auth.
Scale from 1 to millions.

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

LLM API rating for Veo3.1 Image-to-Video

★ 2.6/ 5.0LLM API rating
50% production adoption · 30% category benchmark · 20% tooling & valueEstimated from published specs

2.5Production adoptionNot yet tracked — no public usage data for this release

3.1Benchmark qualityScored on multimodal input support and context

2.0Developer ecosystemContext window, tool and JSON support, price against the category median

Vision & multimodal 2.6

How is this rating calculated?

Every model gets a separate 1.0–5.0 score for each category it can be used in, so a model can rate high for coding and lower for vision. The score combines three parts:

Production adoption — 50%. How widely the model is actually used in production: provider traffic, LiteLLM and gateway usage, open-weight downloads and its LMArena rank. Proven, widely used models score highest.
Category benchmark — 30%. The public benchmark that matters for that category — the Artificial Analysis Intelligence Index and LMArena Elo for reasoning, LMArena coding Elo for coding, image and document support plus vision Elo for vision, tool and JSON support for function calling, measured speed for voice.
Tooling & value — 20%. Context window, support for tools, structured outputs and streaming, and price compared with the category median.

Scores of 4.0 and above are shown in green, 3.0–3.9 in yellow, below 3.0 in red. When a model has no public data for a part, it gets a neutral value instead of an invented number.

A “Verified benchmark” mark (✓) means an independent lab — LMArena or Artificial Analysis — has actually tested that model, and the source figure is shown. Models without that mark are labelled “Estimated from published specs”: the score comes from the published context window, tool and schema support, price and adoption only, because no independent lab has tested them yet.

One exception: a brand-new top-tier model that scores very high on the independent benchmarks but has no usage history yet is rated on the benchmark (60%) and tooling & value (40%) alone, so a missing adoption figure can't hold it back. All inputs come from public sources and are refreshed weekly.

Adoption and benchmark inputs come from public sources — LMArena, Artificial Analysis Intelligence Index and published model specs. Updated weekly.

COMMUNITY

What creators say about AI video models

LMArena—Speed—Sources: LMArena, Artificial Analysis

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

COMMUNITY

What developers say about Veo3.1 Image-to-Video

Summarised from public developer discussions and write-ups. Opinions are the sources’, not LLM.API’s.

Developers on Hugging Face report mixed results with facial consistency, noting the model may alter faces significantly or apply creative interpretations, such as aging a subject to fit a historical filter.
Developers utilizing ComfyUI nodes appreciate the model's versatility, highlighting features like frame interpolation between two images, 4K upscaling capabilities, and the convenience of native synchronized audio generation.
Technical guides for developers emphasize that maintaining structural stability and preventing 'drifting' requires high-quality source images, fixed camera settings, and specific prompt engineering like 'consistent face' or 'stable structure'.

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/

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Veo3.1 Image-to-Video API: Endpoint & Pricing

What is Veo3.1 Image-to-Video?

Can you self-host Veo3.1 Image-to-Video?

Providers

Try this model

Code snippet

Supported endpoints & features

Errors & fallback routing

Veo3.1 Image-to-Video in production

Storyboard acceleration

Iterative creatives

Short-form content

Cinematic prompting

Resolution options

Unified AI Routing

Cost Control

Reliability Layer

Observability

Drop-in SDKs

Model Breadth