Happy Horse 1.1 API
Alibaba Happy Horse 1.1 - cinematic 3-15 second video from text, a first-frame image or up to 9 reference images, at 480p, 720p or 1080p, with smooth camera movement and strong prompt fidelity.
Four endpoints: alibaba/happyhorse-1.1/text-to-video turns a prompt into a clip, image-to-video animates a first frame, reference-to-video builds a new clip from 1 to 9 reference images, and video-extend continues an existing video. Clips run 3 to 15 seconds at 480p, 720p (default) or 1080p, billed per second of output.
Overview
About the Happy Horse 1.1 API
What Happy Horse 1.1 does, how it fits in the Alibaba model lineup, and why teams reach for it.
Happy Horse 1.1 is a video generation model from Alibaba, available through the WaveSpeedAI REST API. Alibaba Happy Horse 1.1 - cinematic 3-15 second video from text, a first-frame image or up to 9 reference images, at 480p, 720p or 1080p, with smooth camera movement and strong prompt fidelity.
Four endpoints: alibaba/happyhorse-1.1/text-to-video turns a prompt into a clip, image-to-video animates a first frame, reference-to-video builds a new clip from 1 to 9 reference images, and video-extend continues an existing video. Clips run 3 to 15 seconds at 480p, 720p (default) or 1080p, billed per second of output.
The Happy Horse 1.1 family on WaveSpeedAI ships 4 REST endpoints covering Text-To-Video, Image-To-Video, Video-Extend, Reference-To-Video workflows. Each variant carries its own pricing, parameter knobs, and example outputs — pick the one that matches your input modality and production constraints, or call several from the same API key to compose multi-step pipelines.
Run Happy Horse 1.1 through the same API key, billing account, and rate-limit envelope you use for the other 1,000+ AI models on WaveSpeedAI. No separate vendor setup, no per-provider SDKs, no per-vendor rate-limit envelopes — one integration covers everything from text-to-image and text-to-video through audio synthesis, 3D generation, upscaling, and editing.
Specs
Happy Horse 1.1 API capabilities and release status
The model-specific details developers search for before choosing an API: availability, expected output length, reference support, and the current live fallback.
Endpoints
4 variants
Text-to-video, image-to-video, reference-to-video and video-extend.
Duration
3-15 s
Any length from 3 to 15 seconds; 5 s is the default.
Resolution
480p / 720p / 1080p
720p is the default.
Price
$0.07-$0.18 / s
480p $0.07, 720p $0.14 and 1080p $0.18 per second of output.
References
Up to 9 images
On reference-to-video, alongside a text prompt.
Endpoints
All Happy Horse 1.1 API endpoints
4 Happy Horse 1.1 endpoints available now on WaveSpeedAI — pick the variant that matches your workflow.
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Happyhorse 1.1 Text To Video
Alibaba HappyHorse 1.1 Text-to-Video generates cinematic 720P or 1080P videos from text prompts, with smooth camera movement, expressive motion, and strong prompt fidelity. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.
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Happyhorse 1.1 Image To Video
Alibaba HappyHorse 1.1 Image to Video animates a reference image into a cinematic 720P or 1080P video, with optional text prompt guidance, smooth camera movement, and expressive, stable motion. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.
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Happyhorse 1.1 Video Extend
Alibaba HappyHorse 1.1 Video Extend extends existing videos with seamless AI-generated continuation, supporting 720P / 1080P output while preserving visual continuity and motion consistency. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.
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Happyhorse 1.1 Reference To Video
Alibaba HappyHorse 1.1 Reference to Video generates new video scenes from reference images, preserving character identity, visual style, and scene consistency. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.
Examples
See Happy Horse 1.1 in action
Real outputs generated by the Happy Horse 1.1 API. Hover any video to preview, click to open the full-size viewer.
How to
How to use the Happy Horse 1.1 API
Four steps from signup to a finished generation. Full Python, Node.js, and cURL examples are in the API section below.
- 01
Get an API key
Sign up for a WaveSpeedAI account and copy your API key from the dashboard. New accounts come with free starter credits — enough to run the playground a few dozen times before billing kicks in.
- 02
Submit a prediction
POST your input as JSON to https://api.wavespeed.ai/api/v3/alibaba/happyhorse-1.1/text-to-video. The endpoint returns a prediction id immediately — generations are async so you don't hold an open connection during inference.
- 03
Poll for completion
GET https://api.wavespeed.ai/api/v3/predictions/{request_id}/result. Return outputs on completed; stop with an error on failed, cancelled, timeout, or deleted; continue polling for every other status.
- 04
Read the output URL
Once status is "completed", read the URL from data.outputs[0]. The URL points to your generated media on the WaveSpeedAI CDN — image, video, audio, or 3D file depending on the Happy Horse 1.1 variant you called.
Use cases
What you can build with Happy Horse 1.1
Common workflows developers and creators use the Happy Horse 1.1 API for.
Text-to-video with smooth camera movement
alibaba/happyhorse-1.1/text-to-video generates cinematic clips from prompts up to 2,500 characters, with expressive motion and stable subjects. Choose 16:9, 9:16, 1:1, 4:3 or 3:4 for ads, social posts and concept work.
Animate a still image
alibaba/happyhorse-1.1/image-to-video uses your image as the first frame and keeps its subject, composition and style while adding motion. A text prompt is optional and can direct the camera and action.
Keep a character consistent across shots
alibaba/happyhorse-1.1/reference-to-video takes 1 to 9 reference images and generates new scenes that keep the characters, outfits and visual style recognizable, which suits series and product content.
Continue a clip
alibaba/happyhorse-1.1/video-extend continues an existing video from where it ends, guided by a prompt, so a short source clip can grow into a longer sequence.
Iterate cheaply at 480p
480p is the lowest-cost tier, so you can test prompts and compositions before spending on 720p or 1080p renders of the final take.
Short-form clips up to 15 seconds
Every endpoint produces 3 to 15 seconds in one pass, long enough for a product reveal, a social hook or a single dialogue-free scene without stitching clips together.
Tips
Tips for prompting Happy Horse 1.1
Practical advice for getting better outputs from Happy Horse 1.1 — drawn from the patterns that work across video models in production pipelines.
- 01
Be specific about camera moves
Mention concrete cinematography vocabulary — orbit, dolly-in, push-in, pan-left, crane shot, handheld follow. Generic prompts produce static or arbitrary camera choices; named camera moves map directly to motion intent in the model's training data and dramatically improve shot quality.
- 02
Anchor character identity with reference images
If your prompt depends on a specific person, character, or product, upload a reference image alongside the prompt. Without a reference, identity drifts across frames and across shots — the same character ends up looking like a slightly different person each generation.
- 03
Describe lighting and time of day
Lighting cues like 'golden hour, soft warm directional light' or 'overcast diffused light, slate-grey sky' improve quality and consistency far more than vague quality modifiers. Lighting is one of the strongest priors the model conditions on.
- 04
Use negative prompts to suppress common failure modes
Useful negatives for video: 'frame flicker, motion blur, watermark, text artifacts, distorted hands, low resolution, jpeg compression'. Negative prompts cost nothing and noticeably reduce the rate of generations you'd otherwise re-roll.
- 05
Pick the shortest duration that captures your beat
Most prompts work best at 5-8 seconds. Longer clips amplify temporal inconsistencies (subject morphing, environment drift). If you need a 20-second sequence, generate three 6-8 second clips and edit them together — quality stays higher than one long generation.
- 06
Match aspect ratio to platform up front
9:16 for TikTok / Reels / Shorts, 16:9 for landscape feeds and YouTube, 1:1 for post grids. Models train slightly differently per aspect ratio — cropping a 16:9 to 9:16 after the fact loses both fidelity and the composition the model intended.
Pricing
Happy Horse 1.1 API pricing
Pricing is per-output. The final charge scales with the parameters you set in each variant's playground (resolution, duration, output count, references).
| Endpoint | Type | Starting price |
|---|---|---|
| alibaba/ | text-to-video | $0.14 |
| alibaba/ | image-to-video | $0.14 |
| alibaba/ | video-extend | $0.14 |
| alibaba/ | reference-to-video | $0.14 |
API
Call the Happy Horse 1.1 API
Sign up for an API key at wavespeed.ai/accesskey, then submit a prediction via REST. The playground generates ready-to-paste samples for any combination of inputs.
POSThttps://api.wavespeed.ai/api/v3/alibaba/happyhorse-1.1/text-to-video
# 1. Submit the prediction.
SUBMIT_RESPONSE=$(curl --silent --show-error --fail-with-body \
-X POST "https://api.wavespeed.ai/api/v3/alibaba/happyhorse-1.1/text-to-video" \
-H "Content-Type: application/json" \
-H "Authorization: Bearer $WAVESPEED_API_KEY" \
-d '{
"prompt": "A cinematic shot of a city at sunset, soft golden light",
"aspect_ratio": "16:9",
"resolution": "720p",
"duration": 5
}')
TASK=$(printf '%s' "$SUBMIT_RESPONSE" | jq 'if has("data") then .data else . end')
PREDICTION_ID=$(printf '%s' "$TASK" | jq -r '.id')
if [ -z "$PREDICTION_ID" ] || [ "$PREDICTION_ID" = "null" ]; then
printf 'Submission response did not contain a prediction id
' >&2
exit 1
fi
RESULT_URL="https://api.wavespeed.ai/api/v3/predictions/$PREDICTION_ID/result"
# 2. Poll until the prediction finishes.
while true; do
RESPONSE=$(curl --silent --show-error --fail-with-body "$RESULT_URL" \
-H "Authorization: Bearer $WAVESPEED_API_KEY")
RESULT=$(printf '%s' "$RESPONSE" | jq 'if has("data") then .data else . end')
STATUS=$(printf '%s' "$RESULT" | jq -r '.status')
case "$STATUS" in
completed) printf '%s\n' "$RESULT" | jq '.outputs'; break ;;
failed|cancelled|timeout|deleted) printf '%s\n' "$RESULT" | jq . >&2; exit 1 ;;
*) sleep 2 ;;
esac
doneconst submitUrl = "https://api.wavespeed.ai/api/v3/alibaba/happyhorse-1.1/text-to-video";
const apiKey = process.env.WAVESPEED_API_KEY;
if (!apiKey) throw new Error('Set WAVESPEED_API_KEY');
async function requestJson(url, options = {}) {
const response = await fetch(url, options);
if (!response.ok) throw new Error(await response.text());
return response.json();
}
// 1. Submit the prediction.
const body = await requestJson(submitUrl, {
method: "POST",
headers: {
"Authorization": `Bearer ${apiKey}`,
"Content-Type": "application/json",
},
body: JSON.stringify({
"prompt": "A cinematic shot of a city at sunset, soft golden light",
"aspect_ratio": "16:9",
"resolution": "720p",
"duration": 5
}),
});
const task = body.data ?? body;
const resultUrl = `https://api.wavespeed.ai/api/v3/predictions/${task.id}/result`;
// 2. Poll until the prediction finishes.
while (true) {
const resultBody = await requestJson(resultUrl, {
headers: { "Authorization": `Bearer ${apiKey}` },
});
const result = resultBody.data ?? resultBody;
if (result.status === "completed") {
console.log(result.outputs);
break;
}
if (["failed", "cancelled", "timeout", "deleted"].includes(result.status)) throw new Error(JSON.stringify(result));
await new Promise(resolve => setTimeout(resolve, 2000));
}import json
import os
import time
from urllib.request import Request, urlopen
api_key = os.environ["WAVESPEED_API_KEY"]
headers = {"Authorization": f"Bearer {api_key}", "Content-Type": "application/json"}
payload = {
"prompt": "A cinematic shot of a city at sunset, soft golden light",
"aspect_ratio": "16:9",
"resolution": "720p",
"duration": 5
}
def request_json(url, data=None):
request = Request(url, data=data, headers=headers, method="POST" if data else "GET")
with urlopen(request) as response:
return json.load(response)
# 1. Submit the prediction.
body = request_json("https://api.wavespeed.ai/api/v3/alibaba/happyhorse-1.1/text-to-video", json.dumps(payload).encode())
task = body.get("data", body)
result_url = f"https://api.wavespeed.ai/api/v3/predictions/{task['id']}/result"
# 2. Poll until the prediction finishes.
while True:
result_body = request_json(result_url)
result = result_body.get("data", result_body)
status = result.get("status")
if status == "completed":
print(result.get("outputs", []))
break
if status in {"failed", "cancelled", "timeout", "deleted"}:
raise RuntimeError(result)
time.sleep(2)Compare
Happy Horse 1.1 vs alternatives
When to pick Happy Horse 1.1 over similar models on WaveSpeedAI.
Happy Horse 1.1 vs Happy Horse 1.0
Happy Horse 1.1 adds a 480p tier and a lower 1080p rate than 1.0. Version 1.0 keeps a video-edit endpoint that 1.1 does not offer.
Happy Horse 1.1 vs Seedance 2.5
Seedance 2.5 reaches 30-second single shots and has video edit and video extend endpoints. Happy Horse 1.1 is the lighter option for clips up to 15 seconds.
Happy Horse 1.1 vs Wan 3.0
Wan 3.0 offers text-, image- and reference-to-video up to 30 seconds. Happy Horse 1.1 covers shorter clips with a 480p tier for inexpensive drafts.
FAQ
Happy Horse 1.1 API — Frequently asked questions
Pricing, license, integration — common questions about running Happy Horse 1.1 on WaveSpeedAI.
What is the Happy Horse 1.1 API?
Happy Horse 1.1 is a Alibaba video generation model exposed as a REST API on WaveSpeedAI. Alibaba Happy Horse 1.1 - cinematic 3-15 second video from text, a first-frame image or up to 9 reference images, at 480p, 720p or 1080p, with smooth camera movement and strong prompt fidelity. You can call it programmatically or try it from the playground linked above.
How do I call the Happy Horse 1.1 API?
Sign up for a WaveSpeedAI account, copy your API key from /accesskey, then POST to https://api.wavespeed.ai/api/v3/alibaba/happyhorse-1.1/text-to-video with your input as JSON. The endpoint returns a prediction id. Poll the result endpoint starting around every 2 seconds, increase the interval for long-running tasks, and stop on any terminal status. Production-oriented Python / Node.js / cURL examples are above.
How much does the Happy Horse 1.1 API cost?
Happy Horse 1.1 starts at $0.14. The exact cost scales with the parameters you set (resolution, duration, output count, references). The live cost preview next to the Generate button in the playground shows the exact price for your current input.
Which Happy Horse 1.1 variants are available?
WaveSpeedAI hosts 4 live Happy Horse 1.1 endpoints: alibaba/happyhorse-1.1/text-to-video, alibaba/happyhorse-1.1/image-to-video, alibaba/happyhorse-1.1/video-extend, alibaba/happyhorse-1.1/reference-to-video. Each variant has its own playground page and pricing.
Can I use Happy Horse 1.1 outputs commercially?
Commercial usage rights follow the Alibaba model license. Most Alibaba models permit commercial output use; see each model's playground page for the specific license summary, and WaveSpeedAI's Terms of Service for platform-level conditions.
Why use Happy Horse 1.1 on WaveSpeedAI instead of going direct?
One API key + one billing account across Happy Horse 1.1 AND 1,000+ other AI models from other providers. No per-vendor SDK setup, no separate rate-limit envelopes, no rewrite-per-vendor integration code. Pricing is typically at parity with or below Alibaba's direct API.
Provider
About Alibaba
The team behind Happy Horse 1.1 and the broader Alibaba model lineup on WaveSpeedAI.
Alibaba's Tongyi Lab produces the Wan family of video models and the Qwen family of LLMs. Wan is notable for being released with open weights, broad variant coverage (text-to-video, image-to-video, reference-to-video, video-edit, video-extend, image-edit, text-to-image), and consistent strength on motion stability and prompt adherence across multilingual prompts.
Start building with Happy Horse 1.1 on WaveSpeedAI
Free starter credits on signup. One API key across 1,000+ AI models from Alibaba and every other provider.