OpenAI

Sora 2 Pro

Name: Sora 2 Pro
Brand: OpenAI
Price: 0.3 USD
Availability: InStock

AI Video Generation Model

Video

OpenAI's professional video generation model with higher resolution support up to 1080p, native audio synthesis, and durations up to 20 seconds

Try Model

20 seconds

Max Video Duration

Supported Modes

Text to Video Image to Video

Active

Details

Model ID

sora-2-pro

Creator

OpenAI

Family

sora

Ready to integrate?

Access sora-2-pro via our unified API.

Create Account

Available at 3 providers

Starting from

$0.300 /second via fal.ai, OpenAI, Replicate

Popular formats

720p (1280×720)

~$0.300

1080p (1920×1080)

~$0.500

high

~$0.500

Prices shown are in USD

See all providers

Providers & Pricing (4)

Sora 2 Pro is available from 4 providers, with per-video pricing starting at $0.3 through fal.ai.

fal.ai

Text to Video

fal/sora-2-pro

Provider Model ID: fal-ai/sora-2/text-to-video/pro

Output

Second 1080p

$0.500

Second 720p

$0.300

View official pricing • As of Mar 13, 2026

fal.ai

Image to Video

fal/sora-2-pro-i2v

Provider Model ID: fal-ai/sora-2/image-to-video/pro

Output

Second 1080p

$0.500

Second 720p

$0.300

View official pricing • As of Mar 13, 2026

OpenAI

Text to Video Image to Video

openai/sora-2-pro

Provider Model ID: sora-2-pro

Output

Second 1080p

$0.500

Second 720p

$0.300

View official pricing • As of Jan 21, 2026

Replicate

Text to Video Image to Video

replicate/sora-2-pro

Provider Model ID: openai/sora-2-pro

Output

Second high

$0.500

Second standard

$0.300

View official pricing • As of Jan 21, 2026

Sora 2 Pro API Async video generation

Access Sora 2 Pro through the Lumenfall API to generate high-resolution video up to 1080p with native audio synthesis and 20-second durations.

Base URL

https://api.lumenfall.ai/v1

Model

sora-2-pro

Code Examples

Text to Video

/v1/videos/generations

# Step 1: Submit video generation request

VIDEO_ID=$(curl -s -X POST \

  https://api.lumenfall.ai/v1/videos \

  -H "Authorization: Bearer $LUMENFALL_API_KEY" \

  -H "Content-Type: application/json" \

  -d '{

    "model": "sora-2-pro",

    "prompt": "",

    "size": "1024x1024"

  }' | jq -r '.id')

echo "Video ID: $VIDEO_ID"

# Step 2: Poll for completion

while true; do

  RESULT=$(curl -s \

    https://api.lumenfall.ai/v1/videos/$VIDEO_ID \

    -H "Authorization: Bearer $LUMENFALL_API_KEY")

  STATUS=$(echo $RESULT | jq -r '.status')

  echo "Status: $STATUS"

  if [ "$STATUS" = "completed" ]; then

    echo $RESULT | jq -r '.output.url'

    break

  elif [ "$STATUS" = "failed" ]; then

    echo $RESULT | jq -r '.error.message'

    break

fi

  sleep 5

done

const BASE_URL = 'https://api.lumenfall.ai/v1';

const API_KEY = 'YOUR_API_KEY';

// Step 1: Submit video generation request

const submitRes = await fetch(`${BASE_URL}/videos`, {

  method: 'POST',

  headers: {

    'Authorization': `Bearer ${API_KEY}`,

    'Content-Type': 'application/json'

},

  body: JSON.stringify({

    model: 'sora-2-pro',

    prompt: '',

    size: '1024x1024'

})

});

const { id: videoId } = await submitRes.json();

console.log('Video ID:', videoId);

// Step 2: Poll for completion

while (true) {

  const pollRes = await fetch(`${BASE_URL}/videos/${videoId}`, {

    headers: { 'Authorization': `Bearer ${API_KEY}` }

});

  const result = await pollRes.json();

  if (result.status === 'completed') {

    console.log('Video URL:', result.output.url);

    break;

  } else if (result.status === 'failed') {

    console.error('Error:', result.error.message);

    break;

  await new Promise(r => setTimeout(r, 5000));

import requests

import time

BASE_URL = "https://api.lumenfall.ai/v1"

API_KEY = "YOUR_API_KEY"

HEADERS = {

    "Authorization": f"Bearer {API_KEY}",

    "Content-Type": "application/json"

# Step 1: Submit video generation request

response = requests.post(

    f"{BASE_URL}/videos",

    headers=HEADERS,

    json={

        "model": "sora-2-pro",

        "prompt": "",

        "size": "1024x1024"

video_id = response.json()["id"]

print(f"Video ID: {video_id}")

# Step 2: Poll for completion

while True:

    result = requests.get(

        f"{BASE_URL}/videos/{video_id}",

        headers=HEADERS

    ).json()

    if result["status"] == "completed":

        print(f"Video URL: {result['output']['url']}")

        break

    elif result["status"] == "failed":

        print(f"Error: {result['error']['message']}")

        break

    time.sleep(5)

Image to Video

/v1/videos/generations

# Step 1: Submit image-to-video request

VIDEO_ID=$(curl -s -X POST \

  https://api.lumenfall.ai/v1/videos \

  -H "Authorization: Bearer $LUMENFALL_API_KEY" \

  -H "Content-Type: application/json" \

  -d '{

    "model": "sora-2-pro",

    "prompt": "",

    "image_url": "https://example.com/start-frame.jpg",

    "duration": "10",

    "aspect_ratio": "16:9"

  }' | jq -r '.id')

echo "Video ID: $VIDEO_ID"

# Step 2: Poll for completion

while true; do

  RESULT=$(curl -s \

    https://api.lumenfall.ai/v1/videos/$VIDEO_ID \

    -H "Authorization: Bearer $LUMENFALL_API_KEY")

  STATUS=$(echo $RESULT | jq -r '.status')

  echo "Status: $STATUS"

  if [ "$STATUS" = "completed" ]; then

    echo $RESULT | jq -r '.output.url'

    break

  elif [ "$STATUS" = "failed" ]; then

    echo $RESULT | jq -r '.error.message'

    break

fi

  sleep 5

done

const BASE_URL = 'https://api.lumenfall.ai/v1';

const API_KEY = 'YOUR_API_KEY';

// Step 1: Submit image-to-video request

const submitRes = await fetch(`${BASE_URL}/videos`, {

  method: 'POST',

  headers: {

    'Authorization': `Bearer ${API_KEY}`,

    'Content-Type': 'application/json'

},

  body: JSON.stringify({

    model: 'sora-2-pro',

    prompt: '',

    image_url: 'https://example.com/start-frame.jpg',

    duration: '10',

    aspect_ratio: '16:9'

})

});

const { id: videoId } = await submitRes.json();

console.log('Video ID:', videoId);

// Step 2: Poll for completion

while (true) {

  const pollRes = await fetch(`${BASE_URL}/videos/${videoId}`, {

    headers: { 'Authorization': `Bearer ${API_KEY}` }

});

  const result = await pollRes.json();

  if (result.status === 'completed') {

    console.log('Video URL:', result.output.url);

    break;

  } else if (result.status === 'failed') {

    console.error('Error:', result.error.message);

    break;

  await new Promise(r => setTimeout(r, 5000));

import requests

import time

BASE_URL = "https://api.lumenfall.ai/v1"

API_KEY = "YOUR_API_KEY"

HEADERS = {

    "Authorization": f"Bearer {API_KEY}",

    "Content-Type": "application/json"

# Step 1: Submit image-to-video request

response = requests.post(

    f"{BASE_URL}/videos",

    headers=HEADERS,

    json={

        "model": "sora-2-pro",

        "prompt": "",

        "image_url": "https://example.com/start-frame.jpg",

        "duration": "10",

        "aspect_ratio": "16:9"

video_id = response.json()["id"]

print(f"Video ID: {video_id}")

# Step 2: Poll for completion

while True:

    result = requests.get(

        f"{BASE_URL}/videos/{video_id}",

        headers=HEADERS

    ).json()

    if result["status"] == "completed":

        print(f"Video URL: {result['output']['url']}")

        break

    elif result["status"] == "failed":

        print(f"Error: {result['error']['message']}")

        break

    time.sleep(5)

Parameter Reference

Required Supported Not available

Core Parameters

Parameter	Type	Description	Modes
`prompt`	string	Required. Text prompt for video generation	T2V I2V
`duration`	number	Video duration in seconds	T2V I2V

Size & Layout

Parameter	Type	Description	Modes
`size`	string	Video dimensions as WxH pixels (e.g. "1920x1080") or aspect ratio (e.g. "16:9") `auto` `1365x768` `768x1365` WxH determines both shape and scale (aspect_ratio and resolution are ignored when size is provided). W:H format is equivalent to aspect_ratio.	T2V I2V
`aspect_ratio`	string	Aspect ratio of the output video (e.g. "16:9", "1:1") `auto` `9:16` `16:9` Controls shape independently of scale. Use with resolution to control both. If size is also provided, size takes precedence. Any ratio is accepted and mapped to the nearest supported value.	T2V I2V
`resolution`	string	Output resolution tier (e.g. "1K", "4K") `auto` `1K` Controls scale independently of shape. Higher tiers produce larger videos and cost more. If size is also provided, size takes precedence for scale. Any tier is accepted and mapped to the nearest supported value.	T2V I2V

Output	`size`		`aspect_ratio` + `resolution`
Flexible
Auto	`"auto"`	—	Model chooses optimal dimensions

1K 2 sizes

Output	`size`		`aspect_ratio` + `resolution`
768 × 1365	`"768x1365"`	or	`"9:16"` + `"1K"`
1365 × 768	`"1365x768"`	or	`"16:9"` + `"1K"`

How these parameters work

size

Exact pixel dimensions

"1920x1080"

aspect_ratio

Shape only, default scale

"16:9"

resolution

Scale tier, preserves shape

"1K"

Priority when combined

size › aspect_ratio + resolution › aspect_ratio › resolution

size is most specific and always wins. aspect_ratio and resolution control shape and scale independently.

How matching works

Shape matching – we pick the closest supported ratio. Ask for 7:1 on a model with 4:1 and 8:1, you get 8:1.

Scale matching – providers use different tier formats: K tiers (0.5K 1K 2K 4K) or megapixel tiers (0.25 1). If the exact tier isn't available, you get the nearest one.

Dimension clamping – if a model has pixel limits, we clamp dimensions to fit and keep the aspect ratio intact.

Output & Format

Parameter	Type	Description	Modes
`n`	integer	Number of videos to generate Default: `1` Gateway generates multiple videos in parallel even if provider only supports 1.	T2V I2V

Additional Parameters

Parameter	Type	Description	Modes
`character_ids` fal	array	Up to two character IDs (from create-character) to use in the video. Refer to characters by name in the prompt. When set, only the OpenAI provider is used.	T2V I2V
`delete_video` fal	boolean	Whether to delete the video after generation for privacy reasons. If True, the video cannot be used for remixing and will be permanently deleted.	T2V I2V
`detect_and_block_ip` fal	boolean	If enabled, the prompt (and image for image-to-video) will be checked for known intellectual property references and the request will be blocked if any are detected.	T2V I2V
`input_reference` replicate	string	An optional image to use as the first frame of the video. The image must be the same aspect ratio as the video.	T2V I2V
`openai_api_key` replicate	string	Optional: Your OpenAI API key. If you use your own OpenAI API key, you will be charged directly by OpenAI.	T2V I2V
`seconds` replicate	integer	Duration of the video in seconds	T2V I2V

Parameter Normalization

How we handle parameters across different providers

Not every provider speaks the same language. When you send a parameter, we handle it in one of four ways depending on what the model supports:

Behavior	What happens	Example
`passthrough`	Sent as-is to the provider	style, quality
`renamed`	Same value, mapped to the field name the provider expects	prompt
`converted`	Transformed to the provider's native format	size
`emulated`	Works even if the provider has no concept of it	n, response_format

Parameters we don't recognize pass straight through to the upstream API, so provider-specific options still work.

Full API Reference Authentication, endpoints, and more

Sora 2 Pro FAQ

How much does Sora 2 Pro cost?

Sora 2 Pro starts at $0.3 per video through Lumenfall. Pricing varies by provider. Lumenfall does not add any markup to provider pricing.

How do I use Sora 2 Pro via API?

You can use Sora 2 Pro through Lumenfall's OpenAI-compatible API. Send requests to the unified endpoint with model ID "sora-2-pro". Code examples are available in Python, JavaScript, and cURL.

Which providers offer Sora 2 Pro?

Sora 2 Pro is available through OpenAI, fal.ai, and Replicate on Lumenfall. Lumenfall automatically routes requests to the best available provider.

Overview

Sora 2 Pro is OpenAI’s high-fidelity video generation model designed for professional creative workflows. It extends the capabilities of the original Sora architecture by supporting 1080p high-definition output, native audio synthesis, and extended shot durations of up to 20 seconds. The model supports both text-to-video generation, where motion is synthesized from natural language prompts, and image-to-video, which uses a static image as a starting frame to guide the visual composition.

Strengths

Temporal Stability: Maintains consistent character features, background elements, and object persistence over a continuous 20-second duration.
Multi-Modal Synthesis: Generates synchronized audio alongside video, reducing the need for external sound design for basic environmental or atmospheric effects.
High-Resolution Output: Supports native rendering up to 1080p, offering significantly more detail in textures and lighting compared to standard-definition latent diffusion models.
Instruction Adherence: Excels at following complex prompts that require specific camera movements (e.g., “dolly zoom” or “tracking shot”) and physics-compliant motion.

Limitations

Prompt Latency: Due to the high parameter count and high-resolution output, generation times are significantly longer than lower-resolution or shorter-form video models.
Synthesizing Physics: While improved, the model may still struggle with complex physical interactions, such as objects shattering or fluid dynamics that require precise causal logic.
Cost: At a starting price of $0.30 per generation, it is more expensive than many lightweight competitors, making it less ideal for rapid, iterative storyboarding.

Technical Background

Sora 2 Pro is built on a transformer-based diffusion architecture that operates on spacetime patches. By treating video frames as sequences of patches rather than individual images, the model can learn spatial and temporal relationships simultaneously. This version incorporates a more robust latent space representative of higher resolutions and an integrated audio head that generates waveforms conditioned on the visual latent representations.

Best For

Sora 2 Pro is best suited for high-end marketing content, high-fidelity cinematic prototyping, and social media production where visual clarity and longer durations are required. It is an ideal choice for creators who need to animate existing concept art via its image-to-video mode or generate high-quality B-roll directly from text. You can experiment with and deploy Sora 2 Pro through Lumenfall’s unified API and interactive playground.

Try Sora 2 Pro in Playground

Generate images with custom prompts — no API key needed.

Open Playground