Hailuo 2.3 Fast by minimax generates high-quality 6s and 10s image-to-video clips at 768p, optimized for creators and marketers. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.
Boşta
$0.19çalıştırma başına·~52 / $10
Motion: The woman naturally raises the perfume bottle from her side toward the camera, tilting it slightly as she rotates her wrist to catch the light. The camera smoothly tracks the product’s motion, performing a gentle forward dolly combined with a slow orbit. When she pauses, the focus subtly shifts to the glowing glass surface. Camera: Perfectly synchronized follow shot with fluid handheld realism. Smooth autofocus transitions and stable depth tracking — no jitter or distortion. The motion arc is wide enough to show dynamic camera behavior but remains physically natural. Lighting: Dynamic reflections move across the bottle as the camera circles. The lighting softly adapts to the new angles, revealing the transparency and shimmer of the glass in realistic detail. Sound: Soft ambient tones, light fabric movement, subtle glass resonance, and a warm, cinematic underscore. Style: Cinematic realism with natural human motion, physically accurate light interaction, and fluid camera following — a clear demonstration of Hailuo 2.3’s precision in temporal coherence and realistic rendering.
Camera: Starts as a low-angle close-up on Wolverine's masked face. He tilts his head back, and the camera shakes slightly as he howls. It then instantly crash-zooms (or rapid dollies) forward as he leaps violently at the camera (towards the enemy). Effect: Wolverine lets out a feral, wide-mouthed howl (visible breath/spit). He then explodes upward and forward from his crouch, kicking up a large cloud of dust and concrete debris from his starting point. His claws are fully extended, gleaming. Intense motion blur trails him as he flies through the air. Sounds/Voices: A loud, iconic, full-throated "BERSERKER ROAR" (the howl). The final, sharp "SNIKT!" as his claws lock in place (no retraction). The explosive sound of shattering rubble as he launches. Mood: Feral, explosive, unrestrained rage, and raw, unstoppable power. Lighting: High-contrast heroic lighting. Dynamic lens flares flash off his claws as he lunges through the air. The dust cloud he creates briefly catches the light.
Camera: A slow, gentle push-in (dolly-in) on the schoolgirl's profile. The camera then subtly pans right, smoothly following the dynamic, billowing curtain as it reveals the cherry blossoms outside the window. Effect: The white curtain forcefully billows and dramatically sways inwards and outwards with distinct gusts of the soft spring breeze coming through the open window. Cherry blossom petals (sakura) frequently drift past the window, some of them visibly caught in the curtain's folds for a moment before floating into the classroom. The girl's hair gently lifts and settles with each passing breeze. Sounds/Voices: Pronounced, rhythmic soft ambient sounds of a gentle spring breeze directly impacting the curtain. The distinct, continuous "whoosh-rustle" of the curtain's fabric is clearly audible. The distant, muffled sounds of a schoolyard (children's laughter, a bell) blend subtly. A very gentle, melancholic piano melody plays softly. Mood: Calm, nostalgic, peaceful, and a touch wistful, typical of a slice-of-life anime. Lighting: Warm, diffused sunlight streams through the window, creating soft, glowing highlights on the girl's hair and the wooden desks. The light gently filters through the cherry blossoms, casting subtle, dappled patterns, and highlights the translucent fabric of the curtain as it moves.
Batman stands stoically on a Gothic rooftop ledge, overlooking a vast, sprawling Gotham City at night. His cape billows dramatically in the wind, a powerful and imposing silhouette against the cityscape. A large, luminous full moon dominates the dark sky above, casting a stark, moody light. The city below is a tapestry of illuminated buildings, glowing streetlights, and a hint of a gritty, urban sprawl. The scene evokes a sense of vigilance, solitude, and iconic heroism. Cinematic, dramatic lighting, wide shot, dark fantasy, superhero, iconic pose, vigilant, atmospheric, blockbuster movie quality.
A passionate male and female dance duo performing a fiery, high-energy Latin dance routine (like Salsa or Cha-Cha). They execute fast, intricate footwork and sensual, rhythmic hip movements with visible chemistry. The man leads the woman through a series of rapid spins and sharp turns, culminating in a dramatic dip where her hair fans out, all under a warm, intense spotlight on a wooden dance floor. Cinematic, passionate, rhythmic, energetic, dynamic lighting, professional dancers, fiery chemistry.
Hailuo 2.3 Fast is the high-speed version of MiniMax’s latest video generation model. It produces cinematic-quality videos 30–50% faster than the standard model while maintaining stable motion, clear detail, and balanced lighting — ideal for creators who need both speed and quality.
| Duration | Resolution | Cost per Job |
|---|---|---|
| 6 seconds | 768p | $0.19 |
| 10 seconds | 768p | $0.32 |
Grab a WaveSpeedAI API key, then call POST https://api.wavespeed.ai/api/v3/minimax/hailuo-2.3/fast 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 Hailuo 2.3 Fast below.
# Submit the prediction
curl -X POST "https://api.wavespeed.ai/api/v3/minimax/hailuo-2.3/fast" \
-H "Content-Type: application/json" \
-H "Authorization: Bearer $WAVESPEED_API_KEY" \
-d '{
"image": "https://example.com/your-input.jpg",
"prompt": "A cinematic shot of a city at sunset, soft golden light",
"duration": 6,
"enable_prompt_expansion": true,
"go_fast": true
}'
# 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("minimax/hailuo-2.3/fast", {
"image": "https://example.com/your-input.jpg",
"prompt": "A cinematic shot of a city at sunset, soft golden light",
"duration": 6,
"enable_prompt_expansion": true,
"go_fast": true
});
console.log(result.outputs[0]); // → URL of the generated output# pip install wavespeed
import wavespeed
output = wavespeed.run(
"minimax/hailuo-2.3/fast",
{
"image": "https://example.com/your-input.jpg",
"prompt": "A cinematic shot of a city at sunset, soft golden light",
"duration": 6,
"enable_prompt_expansion": true,
"go_fast": true
}
)
print(output["outputs"][0]) # → URL of the generated outputHailuo 2.3 Fast is a MiniMax model for video generation from images, exposed as a REST API on WaveSpeedAI. Hailuo 2.3 Fast by minimax generates high-quality 6s and 10s image-to-video clips at 768p, optimized for creators and marketers. 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/minimax/minimax-hailuo-2.3-fast.
Hailuo 2.3 Fast starts at $0.19 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`, `enable_prompt_expansion`, `go_fast`. 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/minimax/minimax-hailuo-2.3-fast.
Average end-to-end generation time on WaveSpeedAI is around 79 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 (MiniMax). The license summary appears on the model card above; see WaveSpeedAI's Terms of Service for platform-level conditions.