HappyHorse Video Generation (Alibaba Cloud)

Complete guide to the Alibaba Cloud HappyHorse-1.1 video generation series: Text-to-Video / Image-to-Video / Reference-to-Video (up to 9 reference images) / Video Edit, unified DashScope async endpoint, high-fidelity subject preservation.

Overview

HappyHorse (快马) is Alibaba’s video generation model series, focused on high-fidelity dynamic video generation — it precisely understands text semantics and outputs smooth, natural, detail-rich, high-quality videos that keep subjects stable. APIYI connects directly through the DashScope passthrough channel, so a single APIYI Key lets you call every HappyHorse capability. The current flagship version, HappyHorse-1.1 (Video Edit remains 1.0), covers four core use cases:

Use case	Model ID	Your input	Output
Text-to-Video	happyhorse-1.1-t2v	A text prompt	Short video
Image-to-Video	happyhorse-1.1-i2v	First-frame image + prompt	Brings a still image to life (no audio-driven support)
Reference-to-Video	happyhorse-1.1-r2v	Up to 9 reference images + prompt	Video with high-fidelity subject and scene preservation
Video Edit	happyhorse-1.0-video-edit	Video + up to 5 reference images + instruction	Locally/globally edited video

🐎 Key highlight: All four capabilities share the same async endpoint and the same request structure — switching use cases only changes the model field. HappyHorse leans toward “high-fidelity dynamic video”; Reference-to-Video supports up to 9 reference images and Video Edit supports up to 5 reference images, with strong subject consistency. It shares the same endpoint as the Wan series and is directly interchangeable.

Text-to-Video API

happyhorse-1.1-t2v, generate video from a pure text prompt.

Image-to-Video API

happyhorse-1.1-i2v, generate video from a first-frame image (no audio-driven).

Reference-to-Video API

happyhorse-1.1-r2v, up to 9 reference images to preserve the subject.

Video Edit API

happyhorse-1.0-video-edit, edit video with up to 5 reference images.

Why Choose APIYI for HappyHorse

One Key for all capabilities

No Alibaba Cloud sign-up, no region configuration. A single APIYI Key calls all four HappyHorse capabilities plus the Wan series.

Direct access, no VPN needed

Connect directly to api.apiyi.com, accessible from domestic data centers and home broadband.

No charge on failure

Tasks that enter the failed state (unreachable media URL, sensitive prompt, etc.) are not billed, so retry with confidence.

DashScope protocol passthrough

Shares the same endpoint and schema as the Wan series; existing Wan code can call HappyHorse just by changing the model name.

Core Features

Four-in-one async endpoint

t2v / i2v / r2v / video-edit share POST /wan/api/v1/...video-synthesis; after submission it returns a task_id, then you poll and download.

High-fidelity subject preservation

The model leans toward a “high-fidelity dynamic video” style, keeping people/objects more stable throughout motion.

Up to 9 reference images

happyhorse-1.1-r2v officially supports up to 9 reference_image entries, giving stronger subject consistency in multi-reference scenarios.

Multiple resolutions and durations

720P / 1080P resolutions, integer durations of 2–15 seconds, and prompt_extend smart rewriting to improve the quality of short prompts.

Supported Models

Model ID	Capability	Required media input	Notes
happyhorse-1.1-t2v	Text-to-Video	None	Pure text generation
happyhorse-1.1-i2v	Image-to-Video	first_frame	Does not support driving_audio
happyhorse-1.1-r2v	Reference-to-Video	reference_image (up to 9)	Multi-reference subject preservation
happyhorse-1.0-video-edit	Video Edit	video + reference_image (up to 5)	Model name has a hyphen

⚠️ Endpoint Selection (Most Important)

APIYI mounts two paths simultaneously, and only the DashScope passthrough endpoint is fully usable for all HappyHorse capabilities:

Path	Protocol style	i2v / r2v availability	Conclusion
/v1/videos	OpenAI flat style	❌ Media fields are dropped	Do not use
/wan/api/v1/services/aigc/video-generation/video-synthesis	DashScope native passthrough	✅ Fully usable	Always use this one

HappyHorse and Wan share the same passthrough endpoint. If you see any doc/example submitting a video task via /v1/videos, ignore it. All create requests go through /wan/api/v1/...video-synthesis, and all queries go through /v1/tasks/{task_id}.

Async Call Flow

The whole flow is asynchronous, in three steps: create task → poll status → download video.

1. Create task

   POST /wan/api/v1/services/aigc/video-generation/video-synthesis, with the request header X-DashScope-Async: enable. It immediately returns a task_id.

2. Poll status

   GET /v1/tasks/{task_id} (with Authorization), querying every 5–10 seconds (not less than 3 seconds), until status becomes completed.

3. Download video

   GET the mp4 directly from the result_url in the response, without the Authorization header (it’s a signed OSS direct link; including Auth will cause a 403).

Task Status Reference

Status	Meaning	Next step
submitted	Submitted, queued	Keep polling
in_progress	Generating	Keep polling (progress often stalls at 30% — that’s the upstream’s coarse reporting granularity, not a stuck task)
completed	Succeeded	Download from result_url
failed	Failed	Check error.message / fail_reason

Complete Python Client

import json, time, urllib.request

BASE = "https://api.apiyi.com"
KEY  = "sk-your-api-key"   # Your APIYI Key

def post(path, body):
    h = {"Authorization": f"Bearer {KEY}", "Content-Type": "application/json",
         "X-DashScope-Async": "enable"}
    req = urllib.request.Request(BASE + path, data=json.dumps(body).encode(), headers=h, method="POST")
    return json.loads(urllib.request.urlopen(req).read())

def get(path):
    req = urllib.request.Request(BASE + path, headers={"Authorization": f"Bearer {KEY}"})
    return json.loads(urllib.request.urlopen(req).read())

# 1. Create task (switching use cases only changes model and media)
r = post("/wan/api/v1/services/aigc/video-generation/video-synthesis", {
    "model": "happyhorse-1.1-t2v",
    "input": {"prompt": "A cat running across a meadow, bright sunshine, camera following"},
    "parameters": {"resolution": "720P", "duration": 5, "prompt_extend": True, "watermark": True}
})
task_id = r["output"]["task_id"]
print("task_id:", task_id)

# 2. Poll (every 5-10 seconds)
while True:
    info = get(f"/v1/tasks/{task_id}")
    status = info["status"]
    print("status:", status, "progress:", info.get("progress"))
    if status == "completed":
        url = info["result_url"]
        break
    if status == "failed":
        raise RuntimeError(info.get("error") or info.get("fail_reason"))
    time.sleep(10)

# 3. Download (do NOT include Authorization! result_url is a signed OSS direct link)
urllib.request.urlretrieve(url, "out.mp4")
print("saved out.mp4")

Key Parameters Explained

When submitting, the body uses the DashScope nested structure: { model, input: { prompt, media[] }, parameters: {...} }.

media[] Types

type	Purpose	Applicable models
first_frame	First-frame image (≤1)	i2v, r2v
reference_image	Reference image (up to 9 for r2v, up to 5 for video-edit)	r2v, video-edit
video	Input video	video-edit

HappyHorse’s i2v does not support driving_audio (audio-driven is a capability exclusive to Wan2.7-i2v). For lip-sync / rap, use Wan2.7.

parameters Fields

Field	Type	Values	Notes
resolution	string	720P / 1080P	Uppercase, explicit specification recommended
duration	int	2–15	Seconds (integer), commonly 5 / 10
prompt_extend	bool	true / false	Smart prompt rewriting, strongly recommended true
watermark	bool	true / false	”AI Generated” watermark in the bottom-right corner
seed	int	0–2147483647	Fixing it improves reproducibility

duration must be an integer 5, not the string "5"; writing resolution in uppercase 720P is more reliable.

How to Choose HappyHorse vs. Wan

HappyHorse and Wan are both Alibaba video models that share the same endpoint and schema (interchangeable by just changing the model name), but they emphasize different things:

Dimension	HappyHorse-1.1	Wan2.7
Audio-driven lip-sync (i2v)	❌ Not supported, i2v is first-frame only	✅ wan2.7-i2v supports driving_audio
Reference-to-Video limit	Up to 9 reference images	Reference images + reference videos combined ≤5
Video Edit reference images	≤5	≤5
Style emphasis	High-fidelity dynamic video, stable subjects	Multi-subject interaction, voice timbre reference

Need multiple reference images to keep the subject consistent → choose happyhorse-1.1-r2v (up to 9). Need lip-sync / rap / digital-human voiceover → choose Wan2.7-i2v (the only one that supports audio-driven).

Best Practices

1. Iterate first at 720P / 5 seconds

   During development, use low-resolution short videos to quickly validate prompts and reference images, then scale up resolution and duration once finalized.

2. Always enable prompt_extend

   prompt_extend: true noticeably improves quality for short prompts.

3. Poll every 5-10 seconds

   Do not go below 3 seconds (you’ll be rate-limited). Each HappyHorse capability at 720P / 5 seconds typically takes 105–115 seconds.

4. Set a 20-minute client timeout as a safety net

   1080P or long videos are significantly slower; set a 20-minute fallback timeout on the polling loop.

5. Download immediately once you get result_url

   result_url expires in 24 hours by default, and it is a signed OSS direct link — do not include the Authorization header when downloading.

Error Codes and Retries

Source	Characteristics	Handling
Create stage (rejected by APIYI)	HTTP 4xx/5xx, with type of task_error / parse_request_failed / build_request_failed	Fix the body and retry (wrong field type, missing media, wrong endpoint)
Execution stage (rejected by upstream Alibaba Cloud)	Task status=failed, with error.message prefixed by a bracketed code like [InvalidParameter] / [InvalidImageUrl]	Read the bracketed hint; usually an unreachable media URL or a sensitive prompt

Recommended client behavior: use exponential backoff retries for HTTP 5xx / network errors; surface HTTP 4xx immediately without retrying; a failed task with [InvalidImageUrl] is retryable, while [InvalidParameter] / sensitive-word failures are not.

FAQ

Is there any difference in how HappyHorse and Wan are integrated?

No. They share the same DashScope passthrough endpoint, the same request structure, the same set of media type names, and the same query endpoint. Switching only changes the model field (e.g., wan2.7-t2v → happyhorse-1.1-t2v); the rest of the body stays identical.

Why can't HappyHorse's i2v do lip-sync?

happyhorse-1.1-i2v does not support the driving_audio (audio-driven) field; i2v only accepts first_frame. For lip-sync / rap / digital-human voiceover, use Wan2.7-i2v.

Can happyhorse-1.1-r2v really take 9 reference images?

Yes. Officially it supports up to 9 reference_image entries — just put them in the media array. More reference images give stronger consistency for the subject / clothing / scene.

Why can't I submit via /v1/videos?

/v1/videos has incomplete support for the media field of i2v / r2v, causing the upstream to report [InvalidParameter] Field required: input.media. All create requests go through /wan/api/v1/services/aigc/video-generation/video-synthesis, and queries go through /v1/tasks/{task_id}.

What if downloading result_url returns a 403?

Remove the Authorization header. result_url is already a signed OSS direct link; adding your APIYI Key gets it rejected by OSS instead. result_url expires in 24 hours by default, so download it promptly.

Are failed tasks billed?

status=failed is not billed. But resubmitting the same task bills again, so handle idempotency.

Group Setup

The HappyHorse and Wan series share a single Wan&HappyHorse group — one Token can call both series. Video models are billed per second, so the Token must meet two conditions to route successfully:

1. Billing model: choose Pay-as-you-go Priority or Pay-as-you-go — video is billed per second, so Pay-per-request Tokens cannot route
2. Group: select a group that includes Wan&HappyHorse

Create Token: set billing model to Pay-as-you-go Priority and group to Wan&HappyHorse (0.14x) to call every Wan2.7 and HappyHorse video model (the screenshot shows the group's former name Wan, since renamed to Wan&HappyHorse)

Pricing

Default price = 98％ of Alibaba’s official price (simple to reason about)

HappyHorse model prices are built into the APIYI system — no manual configuration needed; the group discount applies automatically. In the console the Wan&HappyHorse group shows a rate of 0.14x, which is denominated in the built-in RMB pricing unit. Because APIYI bills in USD at a fixed 1:7 exchange rate, the effective conversion is:

0.14 (RMB pricing unit) × 7 (fixed exchange rate) = 0.98

In other words, the default price = 98% of Alibaba’s official price — cheaper than buying direct from Alibaba, with no overseas link to build yourself.

Conversion: USD price per second = official RMB price × 0.14 (i.e. × 0.98 ÷ 7).

Price detail (default price, billed per second)

HappyHorse-1.1 text-to-video / image-to-video / reference-to-video are priced the same, with two tiers — 720P / 1080P (480P is not supported):

Resolution	Official price	Our default /s	5 s	10 s	12 s
720P	¥0.9/s	$0.126/s	$0.63	$1.26	$1.51
1080P	¥1.6/s	$0.224/s	$1.12	$2.24	$2.69

• happyhorse-1.0-video-edit output duration follows the source video and is billed by actual output seconds, not by duration.
• Prices shown are the default (98% of official); with the maximum top-up bonus, the effective price is roughly the table value ÷ 1.2 (e.g. 1080P 5 s $1.12 → about $0.93).

Stack top-up bonuses for an even lower effective price

After joining the top-up bonus program, credited balance can be boosted up to ~1.2x, pushing the effective price lower still:

0.98 ÷ 1.2 ≈ 0.816

So large customers can reach as low as ~81% of the official price (0.98 ÷ 1.2 ≈ 0.816).

Tier	Effective price (vs Alibaba official)	Formula
Default	98%	rate 0.14x × fixed exchange rate 7
With top-up bonuses (max tier for large customers)	~81.6%	0.98 ÷ 1.2

• Billing dimension = resolution tier × duration (seconds); failed tasks are not billed.
• 1:7 is a fixed settlement exchange rate (not a preferential rate); it applies uniformly to all USD top-ups.
• For the highest bonus tiers and eligible channels, see top-up bonuses. The latest rate is authoritative in the console.

Related Documentation

Text-to-Video Playground

happyhorse-1.1-t2v online debugging

Image-to-Video Playground

happyhorse-1.1-i2v first-frame generation

Reference-to-Video Playground

happyhorse-1.1-r2v up to 9 reference images

Video Edit Playground

happyhorse-1.0-video-edit outfit swap / background swap

Wan Series

Also Alibaba’s, model selection comparison

The HappyHorse series is provided via the APIYI DashScope passthrough channel. For questions or suggestions, please submit a ticket in the APIYI Console.