Luma Ray 2 Flash I2V turns images into high-quality videos with advanced prompt optimization and multi-size output options. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.
Idle
$0.2per run·~50 / $10
A girl lying in a field of dandelions, wind gently blowing her hair, golden hour sunlight, dreamlike slow motion, soft focus
Teen girl decorating her bedroom with fairy lights, polaroids on the wall, plants on the windowsill, cozy vibes and indie music in the background
Mother preparing breakfast in a sunlit kitchen, eggs sizzling in a pan, toast popping up, cereal boxes and kids running around in pajamas
Cyclist riding through a quiet residential street, dogs barking in the distance, birds flying overhead, golden hour shadows stretching long
Walking through a grocery store, slow-motion cart wheels, colorful produce, ambient supermarket sounds, cashier scanning items
Man sipping coffee at a train station platform, trains passing in the background, wind fluttering coat, contemplative mood
College students walking across campus, backpacks swinging, friends laughing, leaves crunching underfoot in autumn sunlight
Late-night study session, laptop glow on student’s face, books scattered on the desk, ticking wall clock and pen scribbling sounds
Quiet dinner at a small Japanese restaurant, soft lantern lighting, sushi being prepared, quiet music and conversations in the air
A fluffy cartoon bunny exploring a magical forest, oversized mushrooms and glowing plants, smooth camera motion, Pixar-style lighting
Transform images into dreamy, cinematic videos at speed with Luma Ray 2 Flash. This fast, efficient model excels at soft, ethereal content with beautiful lighting and gentle motion — perfect for lifestyle content, nature scenes, and emotionally resonant storytelling.
Looking for maximum quality? Try Luma Ray 2 I2V for premium output.
| Parameter | Required | Description |
|---|---|---|
| image | Yes | Source image to animate (upload or public URL). |
| prompt | Yes | Text description of the motion and atmosphere you want. |
| size | No | Output dimensions: 1280×720 (landscape) or 720×1280 (portrait). Default: 1280×720. |
| duration | No | Video length: 5 or 10 seconds. Default: 5. |
Per 5-second billing based on duration.
| Duration | Calculation | Cost |
|---|---|---|
| 5 seconds | 5 ÷ 5 × $0.20 | $0.20 |
| 10 seconds | 10 ÷ 5 × $0.20 | $0.40 |
| Size | Orientation | Best For |
|---|---|---|
| 1280×720 | Landscape | YouTube, presentations, cinematic content |
| 720×1280 | Portrait | TikTok, Instagram Reels, Stories, mobile |
Grab a WaveSpeedAI API key, then call POST https://api.wavespeed.ai/api/v3/luma/ray-2-flash-i2v with your input as JSON. The endpoint returns a prediction id; poll the prediction endpoint until status flips to completed, then read the output URL from data.outputs[0]. Examples for Ray 2 Flash I2v below.
# Submit the prediction
curl -X POST "https://api.wavespeed.ai/api/v3/luma/ray-2-flash-i2v" \
-H "Content-Type: application/json" \
-H "Authorization: Bearer $WAVESPEED_API_KEY" \
-d '{
"prompt": "A cinematic shot of a city at sunset, soft golden light",
"image": "https://example.com/your-input.jpg",
"size": "1280*720",
"duration": 5
}'
# Response includes a prediction id. Poll for the result:
curl -X GET "https://api.wavespeed.ai/api/v3/predictions/{request_id}/result" \
-H "Authorization: Bearer $WAVESPEED_API_KEY"
# When status is "completed", read the output from data.outputs[0].// npm install wavespeed
const WaveSpeed = require('wavespeed');
const client = new WaveSpeed(); // reads WAVESPEED_API_KEY from env
const result = await client.run("luma/ray-2-flash-i2v", {
"prompt": "A cinematic shot of a city at sunset, soft golden light",
"image": "https://example.com/your-input.jpg",
"size": "1280*720",
"duration": 5
});
console.log(result.outputs[0]); // → URL of the generated output# pip install wavespeed
import wavespeed
output = wavespeed.run(
"luma/ray-2-flash-i2v",
{
"prompt": "A cinematic shot of a city at sunset, soft golden light",
"image": "https://example.com/your-input.jpg",
"size": "1280*720",
"duration": 5
}
)
print(output["outputs"][0]) # → URL of the generated outputRay 2 Flash I2v is a Luma model for video generation from images, exposed as a REST API on WaveSpeedAI. Luma Ray 2 Flash I2V turns images into high-quality videos with advanced prompt optimization and multi-size output options. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing. You can call it programmatically or try it from the playground above.
POST your input parameters to the model's REST endpoint (shown in the API tab of this playground) with your WaveSpeedAI API key in the Authorization header. Submission returns a prediction ID; poll the prediction endpoint until status flips to "completed", then read the output URL from the result. The playground generates a ready-to-paste code sample in Python, JavaScript, or cURL for whatever inputs you've set. Full request/response shape is documented at https://wavespeed.ai/docs/docs-api/luma/luma-ray-2-flash-i2v.
Ray 2 Flash I2v starts at $0.20 per run. That figure is the base price — the final charge scales with the parameters you set in the form (output size, length, count, references, or whatever knobs this model exposes), so a higher-quality or larger output costs more than a minimal one. The exact cost for your current input is shown live next to the Generate button before you submit, and the actual per-call charge is recorded on the prediction afterwards.
Key inputs: `prompt`, `image`, `duration`, `size`. The full JSON schema (types, defaults, allowed values) is rendered above the Generate button and mirrored in the API reference at https://wavespeed.ai/docs/docs-api/luma/luma-ray-2-flash-i2v.
Average end-to-end generation time on WaveSpeedAI is around 59 seconds per request — measured across recent runs. Queue time scales with global demand; live status is visible in the prediction record.
Commercial usage rights depend on the model's license, set by its provider (Luma). The license summary appears on the model card above; see WaveSpeedAI's Terms of Service for platform-level conditions.