How do I call HappyHorse-1.1-I2V via API?

Send OpenAI-compatible requests to https://api.llmapi.ai/v1 with model "happyhorse-1.1-i2v" and your LLM.API key. See the code snippet on this page.

Where is the canonical page for HappyHorse-1.1-I2V?

https://llmapi.ai/models/happyhorse-1-1-i2v/

What is the context length for HappyHorse-1.1-I2V?

Reported context for HappyHorse-1.1-I2V is See provider specs. Always verify the active provider row if multiple providers are listed.

Can I use tools or structured outputs with HappyHorse-1.1-I2V?

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

How is HappyHorse-1.1-I2V priced on LLM.API?

Listed pricing metadata shows: 1080p: $0.18/sec; 720p: $0.14/sec. Confirm live rates in the LLM.API dashboard or docs before production budgeting.

What modalities does HappyHorse-1.1-I2V support?

HappyHorse-1.1-I2V accepts text, image and produces video according to its architecture metadata on LLM.API.

Is HappyHorse-1.1-I2V a chat model?

No—HappyHorse-1.1-I2V is categorized as a video model. Use the matching API surface rather than assuming chat completions.

Which endpoint do I call for HappyHorse-1.1-I2V?

POST https://api.llmapi.ai/v1/chat/completions with model "happyhorse-1.1-i2v" and your LLM.API key. The request and response bodies are OpenAI-compatible.

How do I switch from OpenAI to HappyHorse-1.1-I2V 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 HappyHorse-1.1-I2V support function calling and structured outputs?

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

HappyHorse-1.1-I2V API: Endpoint & 60% Discount

Up to 60%

Create short generative video with HappyHorse-1.1-I2V on LLM.API, with resolution-aware pricing and a unified developer workflow.

Start Using API

What is HappyHorse-1.1-I2V?

HappyHorse-1.1-I2V is a generative video model available through LLM.API as `happyhorse-1.1-i2v`. Video generation model by Alibaba. Expect text, image prompts and video outputs, with pricing often tied to seconds and resolution.

Can you self-host HappyHorse-1.1-I2V?

No. We found no public weights for HappyHorse-1.1-I2V 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, up to 60% below list price.

Get API key See API code ↓

Providers

LLM.API routes HappyHorse-1.1-I2V to the providers below, with discounted effective rates versus list price.

List price by provider

InputOutput

alibaba$0 in

$0.0002 out

fal.ai$0 in

$0.0002 out

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

Provider	Pricing	Context	Capabilities
alibaba60% off	in —; out $0.0002 per second of video	—	vision, streaming
fal.ai	in —; out $0.0002 per second of video	—	vision

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

Try this model

Test HappyHorse-1.1-I2V right here — free to start.

HappyHorse-1.1-I2V

Hi! Want to test the model?

Suggestions for your first prompt

Code snippet

Call HappyHorse-1.1-I2V 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 happyhorse-1.1-i2v 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": "happyhorse-1.1-i2v",
    "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="happyhorse-1.1-i2v",
    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: "happyhorse-1.1-i2v",
  messages: [
    { role: "user", content: "Give me three crisp launch checklist items." },
  ],
});

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

stream = client.chat.completions.create(
    model="happyhorse-1.1-i2v",
    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": "happyhorse-1.1-i2v",
  "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 happyhorse-1.1-i2v · 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	Supported	`stream: true`
Vision (image input)	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.

HappyHorse-1.1-I2V in production

Best workloadsLLM.API features

What the model is good at.

Text-to-video generation
Synthesizes short video clips from prompts for ads, explainers, and social. Grounded in the model's video role rather than generic chat claims.
Storyboard acceleration
Turns written beats into moving drafts for rapid review. Reflects video generation positioning for this endpoint.
Cinematic prompting
Responds to camera, lighting, and mood language in creative briefs. Relevant for `happyhorse-1.1-i2v` workloads on LLM.API.
Iterative creatives
Enables prompt-based A/B exploration of motion concepts. Tuned to how teams typically call HappyHorse-1.1-I2V.
Short-form content
Fits vertical and horizontal short-form marketing formats. Relevant for `happyhorse-1.1-i2v` workloads on LLM.API.

What you get when you call HappyHorse-1.1-I2V through LLM.API.

Unified AI Routing
Reach HappyHorse-1.1-I2V 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 HappyHorse-1.1-I2V.
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 HappyHorse-1.1-I2V alongside the rest of your stack.
See every token, everywhere.
Drop-in SDKs
Keep using familiar OpenAI client patterns with base URL https://api.llmapi.ai/v1.
Think tasks, not models.
Model Breadth
Practical: Swap HappyHorse-1.1-I2V 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 (HappyHorse-1.1-I2V)
You are building short-form generative video features (HappyHorse-1.1-I2V)
You need resolution-tiered pricing for motion content (HappyHorse-1.1-I2V)

Avoid if...

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

LLM API rating for HappyHorse-1.1-I2V

★ 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 HappyHorse-1.1-I2V.

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 HappyHorse-1.1-I2V

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

Developers on GitHub and ComfyUI report that HappyHorse-1.1-I2V includes new mandatory image validation for API calls, enforcing specific minimum dimensions and aspect-ratio constraints on input images.
Technical documentation highlights significant improvements in visual quality, specifically noting smoother motion, more natural skin textures, and enhanced facial realism in close-up shots compared to version 1.0.
Developers utilizing the API observe that the model now supports synchronized audio-video output in a single pass, featuring improved lip-sync accuracy and background soundscapes controlled by prompts.

SOURCES

Frequently Asked Questions

How do I call HappyHorse-1.1-I2V via API?
Send OpenAI-compatible requests to https://api.llmapi.ai/v1 with model "happyhorse-1.1-i2v" and your LLM.API key. See the code snippet on this page.
Where is the canonical page for HappyHorse-1.1-I2V?
https://llmapi.ai/models/happyhorse-1-1-i2v/
What is the context length for HappyHorse-1.1-I2V?
Reported context for HappyHorse-1.1-I2V is See provider specs. Always verify the active provider row if multiple providers are listed.
Can I use tools or structured outputs with HappyHorse-1.1-I2V?
Tooling support varies; for pure video models, prefer the modalities listed rather than assuming chat tools.
How is HappyHorse-1.1-I2V priced on LLM.API?
Listed pricing metadata shows: 1080p: $0.18/sec; 720p: $0.14/sec. Confirm live rates in the LLM.API dashboard or docs before production budgeting.
What modalities does HappyHorse-1.1-I2V support?
HappyHorse-1.1-I2V accepts text, image and produces video according to its architecture metadata on LLM.API.
Is HappyHorse-1.1-I2V a chat model?
No—HappyHorse-1.1-I2V is categorized as a video model. Use the matching API surface rather than assuming chat completions.
What is HappyHorse-1.1-I2V?
Video generation model by Alibaba. On LLM.API it is addressed as `happyhorse-1.1-i2v`.

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HappyHorse-1.1-I2V API: Endpoint & 60% Discount

What is HappyHorse-1.1-I2V?

Can you self-host HappyHorse-1.1-I2V?

Providers

Try this model

Code snippet

Supported endpoints & features

Errors & fallback routing

HappyHorse-1.1-I2V in production

Text-to-video generation

Storyboard acceleration

Cinematic prompting

Iterative creatives

Short-form content

Unified AI Routing

Cost Control

Reliability Layer

Observability

Drop-in SDKs

Model Breadth