How to Use Vidu for Text-to-video generation

All-in-one AI image and video generator with reference-to-video, image-to-video, templates, and fast generation for creators. Confirm live details on vidu.com before production use.

Practical Text-to-video generation examples

Example 1

Scenario:
Vidu — Text-to-video generation (pass 1). Context: All-in-one AI image and video generator with reference-to-video, image-to-video, templates, and fast generation for creators.

Objective:
Deliver a reviewable text-to-video generation result using Vidu.

Inputs:
- Verified facts from vidu.com
- Audience, channel, or technical constraints
- Success criteria and forbidden claims
- Relevant product surfaces: Video Generation, Image Generation

Workflow:
Open Vidu → Configure for text-to-video generation → Pilot with sample inputs → Review against success criteria → Iterate one axis → Finalize

Requirements:
- Use only verified Vidu capabilities; do not invent features.
- Confirm live details on vidu.com before promising volume or pricing.
- Human-review before external publish, send, billing, or compliance use.

Expected output:
A concrete text-to-video generation artifact plus a short verification checklist.

Example 2

Scenario:
Vidu — Text-to-video generation (pass 2). Context: All-in-one AI image and video generator with reference-to-video, image-to-video, templates, and fast generation for creators.

Objective:
Deliver a reviewable text-to-video generation result using Vidu.

Inputs:
- Verified facts from vidu.com
- Audience, channel, or technical constraints
- Success criteria and forbidden claims
- Relevant product surfaces: Video Generation, Image Generation

Workflow:
Open Vidu → Configure for text-to-video generation → Pilot with sample inputs → Review against success criteria → Iterate one axis → Finalize

Requirements:
- Use only verified Vidu capabilities; do not invent features.
- Confirm live details on vidu.com before promising volume or pricing.
- Human-review before external publish, send, billing, or compliance use.

Expected output:
A concrete text-to-video generation artifact plus a short verification checklist.

Example 3

Scenario:
Vidu — Text-to-video generation (pass 3). Context: All-in-one AI image and video generator with reference-to-video, image-to-video, templates, and fast generation for creators.

Objective:
Deliver a reviewable text-to-video generation result using Vidu.

Inputs:
- Verified facts from vidu.com
- Audience, channel, or technical constraints
- Success criteria and forbidden claims
- Relevant product surfaces: Video Generation, Image Generation

Workflow:
Open Vidu → Configure for text-to-video generation → Pilot with sample inputs → Review against success criteria → Iterate one axis → Finalize

Requirements:
- Use only verified Vidu capabilities; do not invent features.
- Confirm live details on vidu.com before promising volume or pricing.
- Human-review before external publish, send, billing, or compliance use.

Expected output:
A concrete text-to-video generation artifact plus a short verification checklist.

Example 4

Scenario:
Vidu — Text-to-video generation (pass 4). Context: All-in-one AI image and video generator with reference-to-video, image-to-video, templates, and fast generation for creators.

Objective:
Deliver a reviewable text-to-video generation result using Vidu.

Inputs:
- Verified facts from vidu.com
- Audience, channel, or technical constraints
- Success criteria and forbidden claims
- Relevant product surfaces: Video Generation, Image Generation

Workflow:
Open Vidu → Configure for text-to-video generation → Pilot with sample inputs → Review against success criteria → Iterate one axis → Finalize

Requirements:
- Use only verified Vidu capabilities; do not invent features.
- Confirm live details on vidu.com before promising volume or pricing.
- Human-review before external publish, send, billing, or compliance use.

Expected output:
A concrete text-to-video generation artifact plus a short verification checklist.

Example 5

Scenario:
Vidu — Text-to-video generation (pass 5). Context: All-in-one AI image and video generator with reference-to-video, image-to-video, templates, and fast generation for creators.

Objective:
Deliver a reviewable text-to-video generation result using Vidu.

Inputs:
- Verified facts from vidu.com
- Audience, channel, or technical constraints
- Success criteria and forbidden claims
- Relevant product surfaces: Video Generation, Image Generation

Workflow:
Open Vidu → Configure for text-to-video generation → Pilot with sample inputs → Review against success criteria → Iterate one axis → Finalize

Requirements:
- Use only verified Vidu capabilities; do not invent features.
- Confirm live details on vidu.com before promising volume or pricing.
- Human-review before external publish, send, billing, or compliance use.

Expected output:
A concrete text-to-video generation artifact plus a short verification checklist.

Checklist before you ship

• Confirm the workflow stays inside verified Vidu capabilities
• Review outputs against vidu.com when accuracy or pricing claims matter
• Keep a short verification list for any claim you would publish externally