How do I call LeonardoAI Motion 2.0 Image-to-Video via API?

Send OpenAI-compatible requests to https://api.llmapi.ai/v1 with model "leonardoai-motion-2.0" and your LLM.API key. See the code snippet on this page.

What modalities does LeonardoAI Motion 2.0 Image-to-Video support?

LeonardoAI Motion 2.0 Image-to-Video accepts text, image and produces video according to its architecture metadata on LLM.API.

Which providers serve LeonardoAI Motion 2.0 Image-to-Video?

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

What are limitations of LeonardoAI Motion 2.0 Image-to-Video?

Like other API models, LeonardoAI Motion 2.0 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 LeonardoAI Motion 2.0 Image-to-Video?

Reported context for LeonardoAI Motion 2.0 Image-to-Video is See provider specs. Always verify the active provider row if multiple providers are listed.

Does LeonardoAI Motion 2.0 Image-to-Video support streaming?

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

When should I choose LeonardoAI Motion 2.0 Image-to-Video?

You can tolerate longer generation times than chat — especially when you specifically need LeonardoAI Motion 2.0 Image-to-Video.

Where is the canonical page for LeonardoAI Motion 2.0 Image-to-Video?

https://llmapi.ai/models/leonardoai-motion-2-0/

Which endpoint do I call for LeonardoAI Motion 2.0 Image-to-Video?

POST https://api.llmapi.ai/v1/chat/completions with model "leonardoai-motion-2.0" and your LLM.API key. The request and response bodies are OpenAI-compatible.

How do I switch from OpenAI to LeonardoAI Motion 2.0 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 LeonardoAI Motion 2.0 Image-to-Video support function calling and structured outputs?

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

LeonardoAI Motion 2.0 Image-to-Video API: Endpoint & Pricing

LeonardoAI Motion 2.0 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 LeonardoAI Motion 2.0 Image-to-Video?

LeonardoAI Motion 2.0 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.

Can you self-host LeonardoAI Motion 2.0 Image-to-Video?

No. We found no public weights for LeonardoAI Motion 2.0 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 LeonardoAI Motion 2.0 Image-to-Video to the providers below, with discounted effective rates versus list price.

List price by provider

InputOutput

muapi$0 in

$0.0001 out

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

Provider	Pricing	Context	Capabilities
muapi	in —; out $0.0001 per second of video	—	—

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

Try this model

Test LeonardoAI Motion 2.0 Image-to-Video right here — free to start.

LeonardoAI Motion 2.0 Image-to-Video

Hi! Want to test the model?

Suggestions for your first prompt

Code snippet

Call LeonardoAI Motion 2.0 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 leonardoai-motion-2.0 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": "leonardoai-motion-2.0",
    "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="leonardoai-motion-2.0",
    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: "leonardoai-motion-2.0",
  messages: [
    { role: "user", content: "Give me three crisp launch checklist items." },
  ],
});

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

stream = client.chat.completions.create(
    model="leonardoai-motion-2.0",
    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": "leonardoai-motion-2.0",
  "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 leonardoai-motion-2.0 · 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.

LeonardoAI Motion 2.0 Image-to-Video in production

Best workloadsLLM.API features

What the model is good at.

Product visualization
Helps visualize products and environments before shoot or 3D work. Relevant for `leonardoai-motion-2.0` workloads on LLM.API.
Resolution options
Supports multiple output resolutions depending on provider pricing tiers. Grounded in the model's video role rather than generic chat claims.
Iterative creatives
Enables prompt-based A/B exploration of motion concepts. Reflects video generation positioning for this endpoint.
Storyboard acceleration
Turns written beats into moving drafts for rapid review.
Cinematic prompting
Responds to camera, lighting, and mood language in creative briefs. Reflects video generation positioning for this endpoint.

What you get when you call LeonardoAI Motion 2.0 Image-to-Video through LLM.API.

Unified AI Routing
Production: Reach LeonardoAI Motion 2.0 Image-to-Video and sibling models through one OpenAI-compatible endpoint.
One endpoint, every model.
Cost Control
Practical: Compare provider price points and keep spend visible as you scale LeonardoAI Motion 2.0 Image-to-Video.
More performance, less spend.
Reliability Layer
Practical: Retry and route across configured providers when a single upstream blips.
Never go dark on users.
Observability
Production: Trace prompts, tokens, and errors for LeonardoAI Motion 2.0 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 LeonardoAI Motion 2.0 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 can tolerate longer generation times than chat (LeonardoAI Motion 2.0 Image-to-Video)
You need resolution-tiered pricing for motion content (LeonardoAI Motion 2.0 Image-to-Video)
You are building short-form generative video features (LeonardoAI Motion 2.0 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

LLM API rating for LeonardoAI Motion 2.0 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 LeonardoAI Motion 2.0 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 LeonardoAI Motion 2.0 Image-to-Video

— No public developer feedback about this model yet.

Frequently Asked Questions

How do I call LeonardoAI Motion 2.0 Image-to-Video via API?
Send OpenAI-compatible requests to https://api.llmapi.ai/v1 with model "leonardoai-motion-2.0" and your LLM.API key. See the code snippet on this page.
What modalities does LeonardoAI Motion 2.0 Image-to-Video support?
LeonardoAI Motion 2.0 Image-to-Video accepts text, image and produces video according to its architecture metadata on LLM.API.
Which providers serve LeonardoAI Motion 2.0 Image-to-Video?
LLM.API currently lists: muapi. Availability can vary by region and account.
What are limitations of LeonardoAI Motion 2.0 Image-to-Video?
Like other API models, LeonardoAI Motion 2.0 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 LeonardoAI Motion 2.0 Image-to-Video?
Reported context for LeonardoAI Motion 2.0 Image-to-Video is See provider specs. Always verify the active provider row if multiple providers are listed.
Does LeonardoAI Motion 2.0 Image-to-Video support streaming?
Streaming depends on the active provider; check the providers table on this page for flags.
When should I choose LeonardoAI Motion 2.0 Image-to-Video?
You can tolerate longer generation times than chat — especially when you specifically need LeonardoAI Motion 2.0 Image-to-Video.
Where is the canonical page for LeonardoAI Motion 2.0 Image-to-Video?
https://llmapi.ai/models/leonardoai-motion-2-0/

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LeonardoAI Motion 2.0 Image-to-Video API: Endpoint & Pricing

What is LeonardoAI Motion 2.0 Image-to-Video?

Can you self-host LeonardoAI Motion 2.0 Image-to-Video?

Providers

Try this model

Code snippet

Supported endpoints & features

Errors & fallback routing

LeonardoAI Motion 2.0 Image-to-Video in production

Product visualization

Resolution options

Iterative creatives

Storyboard acceleration

Cinematic prompting

Unified AI Routing

Cost Control

Reliability Layer

Observability

Drop-in SDKs

Model Breadth