Pruna AI P-Video Text to Video API

Pruna AI P-Video Text-to-Video

Pruna AI P-Video Text-to-Video generates videos from natural-language prompts with control over aspect ratio, duration, resolution, audio output, and seed-based reproducibility. It is suitable for cinematic scenes, commercial visuals, social content, concept videos, and other prompt-driven video generation workflows.

Why Choose This?

• Prompt-based video generation Turn natural-language scene descriptions into motion video clips with controllable style and composition.

• Flexible format control Choose aspect ratio, duration, and resolution to match different delivery needs.

• Optional audio saving Enable save_audio when you want the generated output saved with audio.

• Seed support for reproducibility Use seed to get more consistent outputs across repeated generations.

• Simple pricing model Cost scales clearly with duration and output resolution.

Parameters

Parameter	Required	Description
prompt	Yes	Text description of the desired video scene, motion, and style.
aspect_ratio	No	Output aspect ratio, such as 16:9.
duration	No	Video duration in seconds.
resolution	No	Output resolution: 720p or 1080p.
save_audio	No	Whether to save the generated video with audio.
seed	No	Random seed for reproducibility. Use the same seed to get more consistent results.

How to Use

1. Write your prompt — describe the subject, environment, motion, camera movement, and overall mood.
2. Choose aspect ratio — select the format that matches your target platform or composition needs.
3. Set duration — choose how long the video should be.
4. Choose resolution — use 720p for lower cost or 1080p for higher quality.
5. Enable audio saving (optional) — turn on save_audio if you want the saved result to include audio.
6. Set a seed (optional) — use a fixed seed for more reproducible generations.
7. Submit — run the model and download the generated video.

Example Prompt

An adult man stands on a vast desert highway under warm sunlight, with distant mountains and dry air haze behind him. Dust moves subtly across the road, his clothes shift gently in the wind, and he looks toward the horizon before turning slightly toward the camera. The camera slowly pulls back to reveal the open landscape. Cinematic commercial travel film, realistic motion, stable identity, warm natural light.

Pricing

Pricing is based on duration and resolution.

Resolution	Per Second
720p	$0.02
1080p	$0.04

Example Costs

Resolution	5s	10s	15s
720p	$0.10	$0.20	$0.30
1080p	$0.20	$0.40	$0.60

Billing Rules

• 720p costs $0.02 per second
• 1080p costs 2× the 720p rate
• Pricing scales linearly with duration
• aspect_ratio, save_audio, and seed do not affect pricing

Best Use Cases

• Cinematic scene generation — Create travel, lifestyle, and atmospheric video clips from prompts.
• Commercial content — Generate ad-like visuals for products, campaigns, and branded storytelling.
• Social media video — Produce short-form clips tailored to different aspect ratios and durations.
• Concept visualization — Turn written ideas into motion previews for pitching and ideation.
• Creative prototyping — Explore multiple directions quickly with prompt and seed control.
• Audio-enabled delivery — Save video outputs with audio when needed for downstream use.

Pro Tips

• Be specific in your prompt about subject, movement, camera behavior, lighting, and mood.
• Use 720p for rapid testing, then switch to 1080p for higher-quality final outputs.
• Keep the same seed when you want to iterate on a concept with more consistent results.
• Shorter durations are useful for fast concept validation before generating longer clips.
• Match aspect_ratio to the final platform, such as widescreen for cinematic layouts.

Notes

• prompt is the only required field.
• Pricing depends on duration and resolution.
• save_audio controls whether the saved video includes audio, but does not affect pricing.
• seed helps with reproducibility but may not guarantee identical results in every case.

Related Models

• Other Pruna AI video generation and image generation models may be useful when you need different quality, speed, or workflow trade-offs.