Bonus: Top up now and we'll double your first deposit — get x2 credits instantly.
Get Started
Sign Up
Sign Up

HappyHorse-1.0-Video-Edit API: Endpoint & 40% Discount

Up to 40%

Create short generative video with HappyHorse-1.0-Video-Edit on LLM.API, with resolution-aware pricing and a unified developer workflow.

Start Using API

What is HappyHorse-1.0-Video-Edit?

HappyHorse-1.0-Video-Edit targets motion content rather than chat. Video generation model by Alibaba. On LLM.API it sits alongside other media models under a single developer account.

Can you self-host HappyHorse-1.0-Video-Edit?

No. We found no public weights for HappyHorse-1.0-Video-Edit 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 30% below list price.

Get API keySee API code ↓

Providers

LLM.API routes HappyHorse-1.0-Video-Edit 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
$0.0003 out

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

ProviderPricingContextCapabilities
alibaba40% offin —; out $0.0002 per second of video—vision
fal.aiin —; out $0.0003 per second of video—vision

Prices and availability from the LLMAPI catalogue, updated nightly. Last updated 8 Oct 2026.

Try this model

Test HappyHorse-1.0-Video-Edit right here — free to start.

HappyHorse-1.0-Video-Edit
Hi! Want to test the model?

Suggestions for your first prompt

Code snippet

Call HappyHorse-1.0-Video-Edit 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-1.0-video-edit 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-1.0-video-edit",
    "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-1.0-video-edit",
    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-1.0-video-edit",
  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-1.0-video-edit",
    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-1.0-video-edit",
  "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-1.0-video-edit · OpenAI-compatible.

  • POST /v1/chat/completionsChat Completions — supported
FeatureStatusHow to set it
Function calling (tools)Not supportedtools, tool_choice
Parallel tool callsNot supportedparallel_tool_calls
JSON modeNot supportedresponse_format: {"type": "json_object"}
Structured outputsNot supportedresponse_format: {"type": "json_schema", …}
StreamingNot supportedstream: true
Vision (image input)Supportedimage_url content parts
Web searchNot supportedweb_search

ERRORS

Errors & fallback routing

CodeWhat it meansWhat to do
401Missing or invalid API key.Send Authorization: Bearer YOUR_LLMAPI_KEY and check the key is active.
429Rate 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.
5xxUpstream 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-1.0-Video-Edit in production

What the model is good at.

  • Resolution options

    Supports multiple output resolutions depending on provider pricing tiers. Tuned to how teams typically call HappyHorse-1.0-Video-Edit.

  • Short-form content

    Fits vertical and horizontal short-form marketing formats. Relevant for `happyhorse-1.0-video-edit` workloads on LLM.API.

  • Product visualization

    Helps visualize products and environments before shoot or 3D work.

  • Text-to-video generation

    Synthesizes short video clips from prompts for ads, explainers, and social. Reflects video generation positioning for this endpoint.

  • Motion coherence

    Targets temporally consistent motion across frames for the requested scene. Reflects video generation positioning for this endpoint.

What you get when you call HappyHorse-1.0-Video-Edit through LLM.API.

  • Unified AI Routing

    Reach HappyHorse-1.0-Video-Edit 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-1.0-Video-Edit.

    More performance, less spend.

  • Reliability Layer

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

    Never go dark on users.

  • Observability

    Practical: Trace prompts, tokens, and errors for HappyHorse-1.0-Video-Edit 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-1.0-Video-Edit 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 are building short-form generative video features (HappyHorse-1.0-Video-Edit)
  • You can tolerate longer generation times than chat (HappyHorse-1.0-Video-Edit)
  • You need resolution-tiered pricing for motion content (HappyHorse-1.0-Video-Edit)

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

LLM API rating for HappyHorse-1.0-Video-Edit

★ 2.5/ 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
2.8Benchmark qualityNo public Arena rank — scored on declared reasoning support
2.0Developer ecosystemContext window, tool and JSON support, price against the category median
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:

  1. 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.
  2. 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.
  3. 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-1.0-Video-Edit.

  • 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-1.0-Video-Edit

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

  • Developers on inference.sh report that the video-edit variant handles physics-driven motion well, noting that objects exhibit realistic weight and fabric drapes naturally compared to competitors.
  • Engineers at AI API Playbook note that the model follows an asynchronous two-step API pattern, which is standard for compute-heavy video tasks requiring task submission followed by status polling.
  • Developers on each::labs emphasize that the editing variant successfully preserves source motion dynamics while allowing for local or global modifications guided by natural language instructions.

SOURCES

Frequently Asked Questions

  • Which providers serve HappyHorse-1.0-Video-Edit?

    LLM.API currently lists: alibaba, fal.ai. Availability can vary by region and account.

  • What is the context length for HappyHorse-1.0-Video-Edit?

    Reported context for HappyHorse-1.0-Video-Edit is See provider specs. Always verify the active provider row if multiple providers are listed.

  • What are limitations of HappyHorse-1.0-Video-Edit?

    Like other API models, HappyHorse-1.0-Video-Edit 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 modalities does HappyHorse-1.0-Video-Edit support?

    HappyHorse-1.0-Video-Edit accepts text and produces video according to its architecture metadata on LLM.API.

  • Does HappyHorse-1.0-Video-Edit support streaming?

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

  • When should I choose HappyHorse-1.0-Video-Edit?

    You are building short-form generative video features — especially when you specifically need HappyHorse-1.0-Video-Edit.

  • How is HappyHorse-1.0-Video-Edit priced on LLM.API?

    Listed pricing metadata shows: 1080p: $0.24/sec; 720p: $0.14/sec. Confirm live rates in the LLM.API dashboard or docs before production budgeting.

  • Where is the canonical page for HappyHorse-1.0-Video-Edit?

    https://llmapi.ai/models/happyhorse-1-0-video-edit/

  • What is HappyHorse-1.0-Video-Edit?

    Video generation model by Alibaba. On LLM.API it is addressed as `happyhorse-1.0-video-edit`.

  • Can I use tools or structured outputs with HappyHorse-1.0-Video-Edit?

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

COMPARE

Competitive Models

Get one key to every model

Swap your API key. Keep your code.

Start for free Talk to sales