Google Veo3
Playground
Try it on WavespeedAI!Sound on: Google’s flagship Veo 3 text to video model, with audio
Features
Veo 3 - Google
Veo3 is Google DeepMind’s latest advancement in text-to-video generation, pushing the boundaries of what AI can create from natural language prompts. With native audio generation, improved prompt adherence, and stunning realism, Veo3 is redefining multimedia content creation.
🔥 Key Features
-
Text to Image and Video
Generate high-fidelity visuals with cinematic detail directly from your text prompts. -
Native Audio Generation
Add ambient noise, sound effects, and dialogue that sync naturally with visuals—no post-production needed. -
Dialogue & Lip-Sync
Generate characters speaking your script with accurate lip-sync, opening doors to AI filmmaking and animated storytelling. -
Game World Creation
Build immersive video game environments from just a sentence—Veo3’s spatial and physics understanding is a game-changer. -
High Prompt Accuracy
Grounded in real-world physics and enhanced by deep prompt comprehension, Veo3 delivers consistent and context-aware outputs. -
Cinematic Quality
Output videos in stunning quality, complete with smooth motion and realistic effects.
🧠 Built by Google DeepMind
Trained by world-class researchers at Google DeepMind, Veo3 is engineered for creators, developers, and visionaries looking to push the limits of AI-generated content.
✨ Prompting Tips (from Google’s Guide)
To get the best results, try these prompt strategies:
-
Shot Composition:
Close-up
,two shot
,over-the-shoulder
-
Lens & Focus:
Macro lens
,shallow focus
,wide-angle lens
-
Genre & Style:
Sci-fi
,romantic comedy
,action movie
-
Camera Motion:
Zoom shot
,dolly shot
,tracking shot
,pan shot
🎬 Example Prompt
Close up shot (composition) of melting icicles (subject) on a frozen rock wall (context) with cool blue tones (ambiance), zoomed in (camera motion) maintaining close-up detail of water drips (action).
Authentication
For authentication details, please refer to the Authentication Guide.
API Endpoints
Submit Task & Query Result
# Submit the task
curl --location --request POST "https://api.wavespeed.ai/api/v3/google/veo3" \
--header "Content-Type: application/json" \
--header "Authorization: Bearer ${WAVESPEED_API_KEY}" \
--data-raw '{
"prompt": "A breaking news ident, followed by a TV news presenter excitedly telling us: We interrupt this programme to bring you some breaking news... Veo 3 is now live on WaveSpeedAI. Then she shouts: Let's go! The TV presenter is an epic and cool punk with pink and green hair and a t-shirt that says 'Veo 3 on WaveSpeedAI'",
"aspect_ratio": "16:9",
"duration": 8,
"resolution": "720p",
"generate_audio": false,
"enable_prompt_expansion": true
}'
# Get the result
curl --location --request GET "https://api.wavespeed.ai/api/v3/predictions/${requestId}/result" \
--header "Authorization: Bearer ${WAVESPEED_API_KEY}"
Parameters
Task Submission Parameters
Request Parameters
Parameter | Type | Required | Default | Range | Description |
---|---|---|---|---|---|
prompt | string | Yes | - | Text prompt for generation; Positive text prompt. | |
aspect_ratio | string | No | 16:9 | - | Aspect ratio of the video. |
duration | integer | No | 8 | 8 | The duration of the generated media in seconds. |
resolution | string | No | 720p | - | Video resolution. |
generate_audio | boolean | No | false | - | Whether to generate audio. |
enable_prompt_expansion | boolean | No | true | - | If set to true, the prompt optimizer will be enabled. |
negative_prompt | string | No | - | Negative prompt for the generation. | |
seed | integer | No | - | -1 ~ 2147483647 | The random seed to use for the generation. |
Response Parameters
Parameter | Type | Description |
---|---|---|
code | integer | HTTP status code (e.g., 200 for success) |
message | string | Status message (e.g., “success”) |
data.id | string | Unique identifier for the prediction, Task Id |
data.model | string | Model ID used for the prediction |
data.outputs | array | Array of URLs to the generated content (empty when status is not completed ) |
data.urls | object | Object containing related API endpoints |
data.urls.get | string | URL to retrieve the prediction result |
data.has_nsfw_contents | array | Array of boolean values indicating NSFW detection for each output |
data.status | string | Status of the task: created , processing , completed , or failed |
data.created_at | string | ISO timestamp of when the request was created (e.g., “2023-04-01T12:34:56.789Z”) |
data.error | string | Error message (empty if no error occurred) |
data.timings | object | Object containing timing details |
data.timings.inference | integer | Inference time in milliseconds |
Result Query Parameters
Result Request Parameters
Parameter | Type | Required | Default | Description |
---|---|---|---|---|
id | string | Yes | - | Task ID |
Result Response Parameters
Parameter | Type | Description |
---|---|---|
code | integer | HTTP status code (e.g., 200 for success) |
message | string | Status message (e.g., “success”) |
data | object | The prediction data object containing all details |
data.id | string | Unique identifier for the prediction, the ID of the prediction to get |
data.model | string | Model ID used for the prediction |
data.outputs | array | Array of URLs to the generated content (empty when status is not completed ) |
data.urls | object | Object containing related API endpoints |
data.urls.get | string | URL to retrieve the prediction result |
data.has_nsfw_contents | array | Array of boolean values indicating NSFW detection for each output |
data.status | string | Status of the task: created , processing , completed , or failed |
data.created_at | string | ISO timestamp of when the request was created (e.g., “2023-04-01T12:34:56.789Z”) |
data.error | string | Error message (empty if no error occurred) |
data.timings | object | Object containing timing details |
data.timings.inference | integer | Inference time in milliseconds |