WaveSpeedAI Wan 2.6 Video Generation

Generate videos using Alibaba's Wan 2.6 model via WaveSpeed AI. Supports text-to-video and image-to-video generation with up to 15 seconds duration at 720p or 1080p. Features audio-guided generation, prompt expansion, multi-shot mode, and configurable seeds. Use when the user wants to create videos from text prompts or animate images.

Generate videos using Alibaba's Wan 2.6 model via the WaveSpeed AI platform. Supports both text-to-video and image-to-video generation with up to 15 seconds of video at up to 1080p resolution.

Setup

Install the open-source CLI once and sign in; the CLI stores the key, so never ask the user to paste an API key into the chat:

bash

npm install -g @wavespeed/cli
wavespeed login          # opens https://wavespeed.ai/accesskey and stores the key
wavespeed status         # confirms you are signed in

For CI or one-off shells, WAVESPEED_API_KEY in the environment also works.

Prefer MCP tools over shell commands? The same platform is exposed by @wavespeed/mcp (npx -y @wavespeed/mcp; tools search_models, get_model_schema, get_price, upload_file, run_model, get_prediction). It shares the CLI's stored login. Every example below maps one-to-one onto run_model with the same model id and input fields.

Quick Start

Text-to-Video

bash

OUTPUT_URL=$(wavespeed run alibaba/wan-2.6/text-to-video \
  -p "A golden retriever running through a field of sunflowers at sunset" \
  --json | jq -r '.outputs[0]')

Image-to-Video

The image parameter accepts an image URL. If you have a local file, pass it with the @path marker and the CLI uploads it and substitutes the hosted URL.

bash

# Upload a local image to get a URL
OUTPUT_URL=$(wavespeed run alibaba/wan-2.6/image-to-video \
  -i image=@./photo.png \
  -p "The person in the photo slowly turns and smiles" \
  --json | jq -r '.outputs[0]')

Existing URLs work as-is:

bash

OUTPUT_URL=$(wavespeed run alibaba/wan-2.6/image-to-video \
  -i image="https://example.com/photo.jpg" \
  -p "The person in the photo slowly turns and smiles" \
  --json | jq -r '.outputs[0]')

API Endpoints

Text-to-Video

Model ID: alibaba/wan-2.6/text-to-video

Generate videos from text prompts.

Parameters

Parameter	Type	Required	Default	Description
prompt	string	Yes	--	Text description of the video to generate
negative_prompt	string	No	--	Text description of what to avoid in the video
audio	string	No	--	Audio URL to guide generation
size	string	No	1280*720	Output size in pixels. One of: 1280*720, 720*1280, 1920*1080, 1080*1920
duration	integer	No	5	Video duration in seconds. One of: 5, 10, 15
shot_type	string	No	single	Shot type. One of: single, multi
enable_prompt_expansion	boolean	No	false	Enable prompt optimizer for enhanced prompts
seed	integer	No	-1	Random seed (-1 for random). Range: -1 to 2147483647

Example

bash

OUTPUT_URL=$(wavespeed run alibaba/wan-2.6/text-to-video \
  -p "A timelapse of a city skyline transitioning from day to night, cinematic" \
  -i negative_prompt="blurry, low quality, distorted" \
  -i size="1920*1080" \
  -i duration=10 \
  -i shot_type="single" \
  -i seed=42 \
  --json | jq -r '.outputs[0]')

Image-to-Video

Model ID: alibaba/wan-2.6/image-to-video

Animate a source image into a video using a text prompt.

Parameters

Parameter	Type	Required	Default	Description
image	string	Yes	--	URL of the source image to animate
prompt	string	Yes	--	Text description of the desired motion/animation
negative_prompt	string	No	--	Text description of what to avoid in the video
audio	string	No	--	Audio URL to guide generation
resolution	string	No	720p	Output resolution. One of: 720p, 1080p
duration	integer	No	5	Video duration in seconds. One of: 5, 10, 15
shot_type	string	No	single	Shot type. One of: single, multi
enable_prompt_expansion	boolean	No	false	Enable prompt optimizer for enhanced prompts
seed	integer	No	-1	Random seed (-1 for random). Range: -1 to 2147483647

Example

bash

OUTPUT_URL=$(wavespeed run alibaba/wan-2.6/image-to-video \
  -i image=@./landscape.png \
  -p "Clouds drift slowly across the sky, water ripples gently" \
  -i negative_prompt="static, frozen, blurry" \
  -i resolution="1080p" \
  -i duration=10 \
  -i shot_type="single" \
  --json | jq -r '.outputs[0]')

Size Options (Text-to-Video)

Size	Orientation	Use Case
1280*720	Landscape 720p	Standard widescreen video
720*1280	Portrait 720p	Mobile/vertical video, stories
1920*1080	Landscape 1080p	Full HD widescreen video
1080*1920	Portrait 1080p	Full HD vertical video

Resolution Options (Image-to-Video)

Resolution	Use Case
720p	Standard quality, faster generation
1080p	Full HD, higher quality

Pricing

Resolution	5 seconds	10 seconds	15 seconds
720p	$0.50	$1.00	$1.50
1080p	$0.75	$1.50	$2.25

Prompt Tips

• Be specific about motion and action: "A bird takes flight from a branch" vs "a bird"
• Include camera movement: "slow pan left", "zoom in", "tracking shot"
• Describe temporal progression: "transitioning from day to night", "flowers slowly blooming"
• Use negative_prompt to avoid artifacts: "blurry, low quality, distorted, static"
• Enable enable_prompt_expansion for automatic prompt enhancement
• For multi shot type, describe distinct scenes for more dynamic videos

CLI tips

bash

# Inspect the live input schema before running (fields, enums, defaults)
wavespeed run alibaba/wan-2.6/text-to-video -h

# Quote the price first
wavespeed price alibaba/wan-2.6/text-to-video -p "..." -i key=value

# Save outputs to disk instead of only printing URLs
wavespeed run alibaba/wan-2.6/text-to-video -p "..." --json --download "./out/{index}.{ext}"

# Local files: prefix the path with @ and the CLI uploads it and passes the hosted URL
wavespeed run alibaba/wan-2.6/text-to-video -i <field>=@./local-file.png --json

# Recover a result if the run was interrupted (the id is in the --json output)
wavespeed show <id>

run --json prints { id, model, prompt, outputs: [url, ...], saved: [path, ...], elapsed_ms, raw }. Read outputs[0] for the result URL.

Security constraints

• Never ask for the key in chat: wavespeed login handles auth; if wavespeed status says signed out, ask the user to run it.
• Local files only via @: bare paths are passed through untouched and the model will reject them. Only @-prefixed values upload.
• No arbitrary URL loading: only pass media URLs the user provided or that came back from a previous run.
• Input validation: only pass parameters documented above; confirm with wavespeed run <model> -h when unsure.