Kwaivgi Kling V2.0 I2V Master

Kwaivgi Kling V2.0 I2V Master

Playground

Kling 2.0 master elevates image-to-video with improved prompts, richer character motion, better visuals and a Multi-Elements Editor. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.

Features

Kling v2.0 I2V Master — kwaivgi/kling-v2.0-i2v-master

Kling v2.0 I2V Master generates short, cinematic videos from a reference image and a motion-focused prompt. Upload a starting image, optionally provide an end_image for better continuity, and describe the action and camera movement to animate the scene with smooth motion and strong visual coherence. Built for stable production use with a ready-to-use REST API, no cold starts, and predictable pricing.

Key capabilities

• Image-to-video generation anchored to a reference image
• Optional end_image support for more controlled transitions and ending consistency
• Prompt-controlled motion: subtle gestures, facial micro-expressions, hair/clothing movement, environment effects
• Cinematic camera movement: push-in, pan, orbit, handheld micro-shake
• Optional negative_prompt to reduce artifacts and unwanted styles

Pricing

Inputs

• image (required): the starting reference image (visual anchor)
• end_image (optional): target end frame reference for smoother continuity
• prompt (required): describe what happens and how the camera moves
• negative_prompt (optional): describe what to avoid (blur, distortions, artifacts)

Parameters

• prompt: motion + scene direction for the clip
• negative_prompt: optional “avoid list”
• image: input image (upload or URL)
• end_image: optional end-frame image (upload or URL)
• guidance_scale: how strongly the result follows your prompt (lower = more natural, higher = more literal)
• duration: video length in seconds

Prompting guide (I2V with end_image)

For best control, write prompts like a director’s brief:

• Subject action: what the main subject does over time (smile, turn, wave, stand up, walk)
• Environment motion: wind in trees, dust, rain, fog, drifting particles
• Camera motion: slow push-in, orbit, gentle pan, steady handheld feel
• Continuity rules: keep identity, outfit, and scene layout consistent; if using end_image, ensure the motion “lands” on that end frame naturally

Example prompts

• A warm, serene park scene. An elderly couple sits on a bench; the wife gently pats her husband’s back, both smiling. Sunlight filters through leaves with soft dappled shadows. Camera slowly pushes in, subtle breeze moves their hair and clothing, natural motion, 5 seconds.
• Portrait outdoors at golden hour. The subject smiles and looks toward the camera, hair sways slightly in the wind. Gentle handheld micro-sway, shallow depth of field, 5 seconds.
• Cozy indoor scene. The subject turns a page in a book, warm lamp lighting, floating dust motes, camera slow orbit, 5 seconds.

Negative prompt examples

• blur, distort, low quality
• jitter, warping, flicker, melted details
• watermark, logo, subtitles, text artifacts

# Submit the task
curl --location --request POST "https://api.wavespeed.ai/api/v3/kwaivgi/kling-v2.0-i2v-master" \
--header "Content-Type: application/json" \
--header "Authorization: Bearer ${WAVESPEED_API_KEY}" \
--data-raw '{
    "guidance_scale": 0.5,
    "duration": 5
}'

# Get the result
curl --location --request GET "https://api.wavespeed.ai/api/v3/predictions/${requestId}/result" \
--header "Authorization: Bearer ${WAVESPEED_API_KEY}"