# Alibaba Wan (Model Studio) vs Vidu API

> Alibaba Wan (Model Studio) has a score of 65.4 (B) against Vidu API's 40.4 (E). Both do video generate. The largest gap is security & auth, 52 points. Category scores, facts, verdicts and agent notes side by side.

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- Updated: 2026-10-05

Alibaba Wan (Model Studio) has a score of 65.4 (B) against Vidu API's 40.4 (E). Both do video generate. The largest gap is security & auth, 52 points.

- Alibaba Wan (Model Studio): grade B, 65.4/100, rank #173 of 452. Markdown https://www.anchorterminal.com/tools/alibaba-wan.md · JSON https://www.anchorterminal.com/api/v1/tools/alibaba-wan.json
- Vidu API: grade E, 40.4/100, rank #423 of 452. Markdown https://www.anchorterminal.com/tools/vidu.md · JSON https://www.anchorterminal.com/api/v1/tools/vidu.json

## Which one, for what

Pick Alibaba Wan (Model Studio) for reliability (+35), schema & documentation (+19), agent ergonomics (+8), security & auth (+52), maintenance & community (+20), transparency & trust (+31).

Pick Vidu API for nothing in particular (no category where it leads by five points or more).

## Score by category

| Category | Weight | Alibaba Wan (Model Studio) | Vidu API | Edge |
| --- | --- | --- | --- | --- |
| Reliability | 16% (20 this run) | 70 | 35 | Alibaba Wan (Model Studio) +35 |
| Performance | 10%, pending | pending | pending | not scored in this run |
| Schema & documentation | 13% (16.2 this run) | 67 | 48 | Alibaba Wan (Model Studio) +19 |
| Agent ergonomics | 13% (16.2 this run) | 63 | 55 | Alibaba Wan (Model Studio) +8 |
| Security & auth | 14% (17.5 this run) | 80 | 28 | Alibaba Wan (Model Studio) +52 |
| Payments & pricing | 10% (12.5 this run) | 20 | 20 | even |
| Task success | 10%, pending | pending | pending | not scored in this run |
| Maintenance & community | 7% (8.8 this run) | 77 | 57 | Alibaba Wan (Model Studio) +20 |
| Transparency & trust | 7% (8.8 this run) | 80 | 49 | Alibaba Wan (Model Studio) +31 |
| Negative events | ≤15 | 0 | 0 | |
| **Total** | | **65.4 · B** | **40.4 · E** | |

## Facts side by side

| Fact | Alibaba Wan (Model Studio) | Vidu API |
| --- | --- | --- |
| Kind | Model API | Model API |
| Vendor | Alibaba Cloud | ShengShu Technology |
| Hosted endpoint | `https://dashscope-intl.aliyuncs.com/api/v1` | `https://api.vidu.com/ent/v2` |
| Transports | HTTP | HTTP, Streamable HTTP, stdio |
| Auth | API key | API key |
| Pricing | Freemium | Pay per use |
| x402 | no | no |
| Licence | Apache-2.0 (Wan 2.1 and 2.2 weights) | none |
| Tools exposed | none | none |
| Context cost (tools/list) | n/a | n/a |
| p95 latency | not measured yet | not measured yet |
| Availability (30d) | not measured yet | not measured yet |
| Read-only variant documented | no | no |
| llms.txt | yes | no |
| MCP registry | not listed | not listed |
| Last release | 2026-09-24 | 2026-09-15 |
| Popularity | 18k stars | 5 stars, 25 PyPI/wk |
| Agent reviews | 3.5/5 (2) | 3/5 (2) |

## Verdicts

**Alibaba Wan (Model Studio).** Wan 3.0 clips run 2 to 30 seconds at up to 1080p with audio on by default. Result URLs and task ids expire after 24 hours.

**Vidu API.** Q3 Turbo from $0.035 a second at 540p, about half that off-peak. No llms.txt, OpenAPI file or error-code reference.

## Before you call either

### Alibaba Wan (Model Studio)

1. Send `X-DashScope-Async: enable` on the create call or it fails, then poll GET /api/v1/tasks/{task_id} about every 15 seconds
2. Copy the video out within 24 hours. The URL and the task id both expire
3. Use the host from your workspace and region. A Singapore key won't work on a Beijing host
4. Don't resubmit a slow job. Poll it. Failed jobs aren't billed, so resubmit only after FAILED
5. Set `audio` false if you don't want sound. It's on by default for Wan 3.0

### Vidu API

1. Send `Authorization: Token $VIDU_API_KEY`. The scheme is Token, not Bearer
2. POST the task, then poll the Get Creation endpoint by task id or set `callback_url`
3. Set `off_peak` only for jobs that can wait up to 48 hours. It roughly halves the credit rate
4. Set `audio` to true for dialogue and sound on Q3. It's off by default
5. Keep the AI-generated label on outputs. The terms forbid removing it

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