Wan 3.0 entered public beta on August 7, 2026. Alibaba now presents it through Wan.video, QwenCloud, and Alibaba Cloud Model Studio, but public beta does not mean unrestricted access, a general-availability release, or downloadable model weights.
That distinction matters. Wan 3.0 is a meaningful step toward longer, audio-native, reference-driven video creation, yet the right choice depends on whether you can enter the beta, whether its per-second pricing fits your workflow, and whether you need cloud access or local control.
In our first-output test, Wan 3.0 followed a controlled five-second paper-boat prompt closely and produced a clean, playable 720P clip. The boat’s left-to-right movement was restrained, and one run cannot establish stability.
GlobalGPT is a multi-model AI subscription workspace for people who want to create with several models in one place. It offers a practical way to compare current video tools without rebuilding the workflow for every model.
Its current Wan options include Wan 2.7 and Wan 2.6. For Wan 3.0, use one of the official beta routes explained on this page.
간단한 답변
Wan 3.0 entered public beta on August 7, 2026. It adds up to 30-second generation, native audio, mixed-reference workflows, and hosted access through official Wan and Alibaba routes.
wan3.0-video빠른 이동
Has Wan 3.0 Been Released?
Yes—as a public beta. . official Wan account announced the beta on August 7, 2026 and directed users to Wan.video, Alibaba Cloud Model Studio, and QwenCloud.
The date is best understood as the public-beta announcement, not a blanket global release. The QwenCloud model page labels the model as beta and presents a Join Beta action, so account access remains part of the process.
For users, “released” now has four separate meanings:
- Announced: the public beta is official.
- Listed: official product and cloud pages show the model.
- Callable: an approved account can submit a supported job.
- Open: model weights can be downloaded and run locally.
Wan 3.0 meets the first two conditions. The third depends on the route and account, while the fourth does not apply to the current release.
What Are the Main Wan 3.0 Features?
Wan 3.0 is positioned as an all-in-one video model rather than a narrowly separated text-to-video tool. Its official pages group reference, editing, replication, and driving capabilities under one model.
The feature set in one view
Longer native generation
Create clips up to 30 seconds, with duration controls varying by route and mode.
Up to 30 secAudio and video together
Direct visual action, dialogue, ambience, and other sound events within one audiovisual workflow.
네이티브 오디오Mixed-reference input
Use text, images, video, audio, files, web pages, or complex images when the selected route exposes them.
Omni-modalGenerate and transform
Bring generation, editing, replication, and motion-driving tasks under the same model identity.
하나의 모델
최대 30초
The headline upgrade is duration. QwenCloud says Wan 3.0 can generate videos up to 30 seconds, while Wan.video describes native 30-second duration with intelligent duration control.
Our 30-second request was accepted and entered processing, but the tested route timed out before returning a video. That run shows an operational reliability limit, not that Wan 3.0 lacks 30-second support.
Native audio and audiovisual timing
Wan promotes picture and sound as one audiovisual workflow. In our five-second café task, the route returned a playable video with a real AAC stereo track, one barista, one cup placement, and a continuous scene.
The result also added malformed Chinese subtitles in the final shot, violating the no-subtitles instruction. We verified the audio stream, but did not independently transcribe the spoken line or audit the clink, hiss, and frame-level synchronization.
T1 · first valid output
Partly meets the task
- Passed: one barista, one white cup, one cup placement, and a continuous scene.
- Partially observed: an audio track exists, but the spoken wording, ceramic clink, steamer hiss, and exact synchronization were not independently audited.
- Failed: a line of unwanted garbled Chinese subtitles appears at the end.
Editorial limit: this output proves delivery of a real stereo track, not perfect speech accuracy or frame-accurate sound synchronization.
View the exact T1 prompt
Character and object consistency
For the consistency test, one woman in a yellow raincoat and round red glasses walked through a rainy market. Her face, clothing colors, proportions, and the visible red umbrella stayed unusually stable throughout the continuous tracking shot.
The multi-step action was incomplete. She turned toward the stall and touched the closed umbrella, but did not pick it up or continue walking while carrying it.
T2 · first valid output
Partly meets the task
- Passed: one woman, stable face and proportions, yellow raincoat, red glasses, left-to-right walk, turn, continuous scene, and no text or duplication.
- Partial: the red umbrella stays recognizable, but she touches it without completing the pickup-and-carry action.
실용적인 교훈: identity persistence was strong; precise completion of a multi-step object interaction was the weak point.
View the exact T2 prompt
Camera and action control
The camera-control task asked one teal-jacket cyclist to ride left to right while the camera slowly pulled backward from a low, side-facing position. The first output maintained the rider, direction, level horizon, and continuous coastal-road scene without adding cars, text, or another cyclist.
This was the cleanest feature result. The pullback was smooth and recognizable, although the rider stayed in a similar horizontal area because the camera tracked alongside.
T3 · first valid output
Meets the task
- Passed: one teal-jacket cyclist, rightward travel, low camera, level horizon, smooth pullback, and one continuous scene.
- Passed: no camera orbit, visible cut, extra cyclist, car, text, or logo.
증거의 범위: this is one strong first output, not proof that the same camera control will repeat reliably.
View the exact T3 prompt
Omni-modal references
The official model description lists audio, images, text, and video among the supported input types. It also says the model can parse files, web pages, and complex images, which expands the workflow beyond writing a prompt from scratch.
For a marketing team, that could mean starting from a launch brief, product image, existing clip, or reference page. For creators, it could reduce the number of tools needed to translate a concept into a consistent sequence.
Editing, replication, and driving workflows
Wan 3.0 brings several creative tasks into one model identity:
- Generate a new scene from text or mixed references.
- Edit or extend the visual direction of existing material.
- Replicate a subject, object, or style across a sequence.
- Drive motion or performance from reference media.
- Combine visual and audio direction in a single job.
These are official capabilities, not a guarantee that every route exposes every control. Choose the route by the input mode you actually need, then check the settings shown for that account before preparing a large batch.
Wan 3.0 vs. Wan 2.x: What Changed?
The most useful distinction is workflow and availability, not a speculative quality score. Wan 3.0 is the new public-beta model centered on longer generation, native audio, and omni-modal reference workflows.
Wan 2.x models are the more established choices already present across existing products. Choose between them based first on the workflow you need and the access you can use today.
Choose by workflow, not version number
Wan 3.0 is the beta route; Wan 2.7 and 2.6 are the practical current route.
| 결정 | Wan 3.0 | Wan 2.7 / 2.6 |
|---|---|---|
| 현재 현황 | Public beta through official Wan and Alibaba routes | Current production choices on platforms including GlobalGPT |
| 공식적인 강조 | Up to 30 seconds, native audio, mixed references, editing and driving | Practical text/image-to-video workflows with broader existing availability |
| 선택해야 할 가장 큰 이유 | You need to evaluate the new long-form, audio-native workflow Choose for new capability | You need to start creating now in a familiar multi-model workspace Choose for access |
| Access trade-off | Beta approval and route-specific controls | Less beta friction on currently supported platforms |
If you are comparing generations rather than release notes, use the same prompt and production goal. Our Sora 2 vs. Wan 2.5 comparison provides useful context on how model choice changes a workflow, but its results should not be transferred to Wan 3.0.
Where Can You Use Wan 3.0?
Start with one of the three routes named by Wan. Each serves a different type of user.
Pick the route that matches the job
All three are official routes, but they solve different access needs.
Wan.video
A visual interface for creators who want to make a video without building an integration.
Best for: hands-on creationQwenCloud
The clearest public source for the model ID, specifications, beta step, rate limits, and pricing.
Best for: budget and API planningModel Studio
An Alibaba Cloud model-market path for application and content-pipeline integration.
Best for: existing cloud workflowsWan.video
Wan.video is the official consumer-facing product page. Its Wan 3.0 call to action leads into the creation surface, where users sign in before starting a job.
Choose this route if you want a visual creation workflow and do not need to build an API integration.
QwenCloud
QwenCloud is the clearest public model page for specifications, pricing, and the exact model ID. It lists wan3.0-video, presents the beta application step, and shows rate limits and API examples.
Choose QwenCloud if you want a documented cloud route and can work through beta access. It is also the cleanest place to calculate a budget before submitting longer or higher-resolution clips.
Alibaba Cloud Model Studio
Alibaba Cloud Model Studio is the developer-oriented option. The public model-market route points to the Singapore region and uses the same official model identity.
Choose Model Studio when Wan generation needs to sit inside a larger application, automated content pipeline, or existing Alibaba Cloud environment.
A practical multi-model workflow in GlobalGPT
If the immediate goal is a finished video rather than entry into a specific beta, GlobalGPT puts current Wan models and other video generators in one workspace. The verified list includes Wan 2.7, Wan 2.6, Veo 3.1, Sora 2, Kling 3.0, and Seedance 2.5.
Keep the comparison focused: use one real prompt, the same aspect ratio, and the first usable result from each model. Compare motion, identity consistency, audio needs, turnaround, and editing effort rather than choosing from reputation alone.
How to Use Wan 3.0
The exact controls vary by product, but the reliable setup sequence is straightforward.
1. Choose the right official route
Use Wan.video for a visual creator workflow, or choose QwenCloud/Model Studio when you need cloud documentation and API integration. Avoid relying on an exact-match domain name alone; confirm that the route is linked by Wan or Alibaba.
2. Confirm the model identity and beta access
For the documented cloud route, look for wan3.0-video. Complete the Join Beta or sign-in step shown by the platform, then confirm that the model is selectable for your account.
3. Pick an input mode
Start from the smallest input set that can express the task:
- 텍스트: a new scene with no visual reference.
- 이미지: preserve a product, subject, composition, or first frame.
- 비디오: guide motion, editing, replication, or continuation.
- File or web page: translate a source brief or page into a video concept.
- 오디오: guide performance or audiovisual structure when the route exposes it.
4. Set duration and resolution deliberately
Use 480P for prompt development because it has the lowest listed per-second rate. Move to 720P or 1080P after the scene, references, and timing are stable; otherwise a small prompt mistake becomes an expensive high-resolution mistake.
5. Write a production-ready prompt
A useful Wan 3.0 prompt should define the subject, action, setting, camera behavior, timing, audio events, and exclusions. Keep the sequence physically possible, especially when requesting a continuous long clip.
- Name one main subject before adding secondary action.
- Describe camera movement in plain, chronological language.
- Assign sound to visible events instead of requesting generic “cinematic audio.”
- State what must remain consistent: face, clothing, product, room, or lighting.
- Exclude unwanted text, logos, extra people, or abrupt cuts.
For more control over shot language, see this guide to AI video camera movement prompts.
6. Review before increasing cost
Check the entire clip, not just the opening frame. Look for identity drift, object changes, impossible motion, missing sound, timing errors, unwanted text, and weak final frames before increasing duration or resolution.
For a broader model decision, take that same prompt to GlobalGPT의 동영상 작업 공간. Comparing the current models on your actual task is more useful than searching for one best model for every job.
Our Wan 3.0 Hands-On Test: The First Output
We tested one controlled text-to-video task through the Anywhere direct HTTP API on August 13, 2026. The goal was narrow: see whether wan3.0-video could produce a usable five-second shot from one frozen prompt without selecting a better-looking reroll.
The first completed video was valid, playable, and kept as the result. We submitted the task once, made no quality retry, and did not run a stability batch.
Hands-on methodology
One frozen request, one first valid output
wan3.0-videoView the exact frozen prompt
The task moved from queued to success in about 213 seconds. Stability was not tested, so this setup supports a first-output judgment only.
First-output result
All seven objective checks passed
| Subject and direction | 패스 — Exactly one red paper boat remained visible and moved from left-of-center toward the middle. The left-to-right travel was real but subtle. |
|---|---|
| Shot and camera | 패스 — One continuous scene, no visible cut, and a stable low camera position. |
| Rain and reflections | 패스 — Rain lines, ripples, and blue/pink-violet reflections stayed coherent across the clip. |
| 제외 사항 | 패스 — No people, text, logos, or extra boats appeared. |
| Technical delivery | 패스 — The video played successfully and matched the requested five-second, 720P, 16:9 format. |
How Much Does Wan 3.0 Cost?
QwenCloud prices Wan 3.0 by generated second and resolution. On August 11, 2026, the model page listed 480P at $0.05 per second, 720P at $0.10 per second, and 1080P at $0.20 per second.
Wan 3.0 price by resolution
QwenCloud rates checked August 11, 2026
USD per generated second
| 해상도 | 요율 | Relative rate | 5초 | 10초 | 30 sec |
|---|---|---|---|---|---|
| 480P | $0.05/s | $0.25 | $0.50 | $1.50 | |
| 720P | $0.10/s | $0.50 | $1.00 | $3.00 | |
| 1080P | $0.20/s | $1.00 | $2.00 | $6.00 |
The pricing scales linearly: 720P costs twice the 480P rate, while 1080P costs four times the 480P rate. A 30-second 1080P clip therefore costs $6.00 at the listed QwenCloud rate, compared with $1.50 at 480P.
These figures apply to QwenCloud, not automatically to Wan.video, Model Studio, GlobalGPT, or another provider. Check the selected route’s current billing unit, account allowance, and failure policy before committing to a batch.
Is Wan 3.0 Open Source? API and Download Options
Wan 3.0 is not presented as an open-source model release. QwenCloud lists “Open Source: No,” and the official Wan GitHub organization did not list a Wan 3.0 weight repository when checked on August 10, 2026.
That does not stop users from accessing the model through hosted services. It does mean the current route is cloud-based rather than a downloadable local-weight workflow.
Wan 3.0 API model ID
The official QwenCloud model ID is wan3.0-video. Its public example includes video-oriented fields such as resolution, ratio, and duration, but the exact request format, authorization, regional endpoint, and available controls should come from the selected official cloud account.
Downloading a video is not downloading the model
“Wan 3.0 download” can describe two different actions:
- Download the generated video: export the finished MP4 from the hosted product.
- Download model weights: install and run the underlying model locally.
The first is a normal output workflow. The second is not part of the current Wan 3.0 release.
Who Should Use Wan 3.0?
Wan 3.0 is most attractive to teams that value its new workflow enough to accept beta access and cloud pricing.
It is a strong candidate for:
- Creators exploring longer single-shot AI videos.
- Teams that want visuals and native audio generated together.
- Marketers working from product images, briefs, files, or web pages.
- Studios that need reference-led identity or style consistency.
- Developers already prepared for a cloud/API workflow.
Choose a current alternative first when:
- You need open weights or fully local processing.
- You cannot wait for beta approval.
- Your production needs stable, established controls more than a new feature set.
- You want to compare several models without maintaining separate workflows.
Our recommendation is simple: enter the official beta if 30-second, audio-native, or mixed-reference creation solves a real production problem. That is where Wan 3.0 offers the clearest reason to accept beta access and cloud pricing.
Otherwise, start with 완 2.7, 완 2.6, or another current model in GlobalGPT. Use the guide to the best AI video generators to narrow the field before committing to a production workflow.
자주 묻는 질문
When was Wan 3.0 released?
Wan announced that the Wan 3.0 public beta was live on August 7, 2026. This is the public-beta announcement date, not a general-availability or open-weight release date.
Is Wan 3.0 available to everyone?
No. Official pages list the model, but QwenCloud presents a Join Beta step and access can depend on the selected route, account, approval, and region.
Where can I use Wan 3.0?
Wan names Wan.video, Alibaba Cloud Model Studio, and QwenCloud as official routes. Wan.video is creator-facing, while QwenCloud and Model Studio are better suited to documented cloud and API workflows.
How long can Wan 3.0 videos be?
The official QwenCloud page says Wan 3.0 can generate videos up to 30 seconds. Available duration controls can vary by route and mode.
Does Wan 3.0 generate audio?
Yes. Wan presents native audio and an integrated audiovisual experience as core Wan 3.0 capabilities.
How much does Wan 3.0 cost?
On August 11, 2026, QwenCloud listed 480P at $0.05 per second, 720P at $0.10 per second, and 1080P at $0.20 per second. Other providers can use different prices or credits.
Is Wan 3.0 open source?
No. The official QwenCloud model page lists Open Source as No, so the current release is a hosted beta rather than an open-weight model package.
Can I download Wan 3.0 model weights?
Not through the current official release. Users can download videos produced by a hosted service, but that is different from downloading the model weights for local use.
What is the Wan 3.0 API model ID?
QwenCloud documents the official model ID as wan3.0-video. Use the regional endpoint and request format provided by the official cloud account.
What can I use for video work now?
GlobalGPT currently offers Wan 2.7 and Wan 2.6 alongside Veo 3.1, Sora 2, Kling 3.0, and Seedance 2.5. Use one prompt across a small set of models and choose the result that best matches your production goal.
Choose the Workflow That Solves Your Real Task
Wan 3.0 is worth following because it combines longer video, native audio, and broader reference inputs in one official beta. The best next step is not to chase every feature at once; choose one job, one route, and one budget.
Bring a real prompt to GlobalGPT and try it with the currently available Wan and video models. Compare the first result, the editing effort, and the final production fit—then invest in the workflow that actually earns its place.
