Sora 2 vs Veo 3 Image-to-Video Comparison: The Essential Difference Between 1 Reference Image vs 2 Start-End Frames

In the field of AI video generation, Image-to-Video is one of the most anticipated features. However, many developers have misconceptions about how Sora 2 and Veo 3 handle image uploads: Can Sora 2 really only use images as the first frame? And how do Veo 3's two images work? This article will dive deep into the core differences between these two models.

Core Value: After reading this article, you'll understand the fundamental difference between Sora 2's reference images and Veo 3's first-last frame approach, and master how to choose the most suitable API based on your creative needs.

Sora 2 vs Veo 3 Image-to-Video Core Differences

Sora 2 Image-to-Video: The Truth About 1 Reference Image

Many people mistakenly believe that Sora 2's image input is the "first frame image" – this is a common misconception. In reality, Sora 2's image serves as a "reference image", which provides visual style, character design, or scene reference for the video, rather than being forcibly locked as the video's first frame.

How Reference Images Work:

1. Style Integration: The reference image's color palette, lighting, and artistic style influence the entire video
2. Character Consistency: Uploading character images maintains consistent character appearance throughout the video
3. Scene Reference: Providing environment images helps the AI understand the desired scene atmosphere
4. Non-Mandatory First Frame: AI decides how to integrate the reference image based on the prompt

Of course, if your prompt explicitly requests "start from this image," Sora 2 will treat it as the first frame. But this is a result of prompt control, not an inherent limitation of the image upload.

Sora 2 Image-to-Video API Guide

Sora 2 Image-to-Video Basic Example

import openai

client = openai.OpenAI(
    api_key="YOUR_API_KEY",
    base_url="https://vip.apiyi.com/v1"
)

# Sora 2 image-to-video - reference image mode
response = client.videos.create(
    model="sora-2",
    prompt="An orange cat lazily stretching in the sunlight, camera slowly zooming in",
    input_reference=open("cat_reference.jpg", "rb"),  # Reference image
    size="1280x720",
    seconds=8
)

import openai
import time

def generate_video_with_reference(
    prompt: str,
    reference_image_path: str,
    model: str = "sora-2",
    size: str = "1280x720",
    seconds: int = 8
) -> dict:
    """
    Generate video using Sora 2 with reference image

    Args:
        prompt: Video description
        reference_image_path: Path to reference image
        model: sora-2 or sora-2-pro
        size: Video dimensions
        seconds: Video duration (4/8/12)
    """
    client = openai.OpenAI(
        api_key="YOUR_API_KEY",
        base_url="https://vip.apiyi.com/v1"
    )

    # Create video generation task
    with open(reference_image_path, "rb") as img_file:
        response = client.videos.create(
            model=model,
            prompt=prompt,
            input_reference=img_file,
            size=size,
            seconds=seconds
        )

    video_id = response.id
    print(f"Video generation task created: {video_id}")

    # Poll until completion
    while True:
        status = client.videos.retrieve(video_id)
        if status.status == "completed":
            return {
                "success": True,
                "video_url": status.video_url,
                "duration": seconds
            }
        elif status.status == "failed":
            return {"success": False, "error": status.error}

        print(f"Generating... Status: {status.status}")
        time.sleep(5)

# Usage example
result = generate_video_with_reference(
    prompt="Character walking down city streets, warm sunlight, cinematic quality",
    reference_image_path="character.jpg"
)

Tip: Call the Sora 2 API through apiyi.com, which provides stable API service and free testing credits for quick validation of image-to-video results.

Veo 3.1 First & Last Frame Control: The 2-Image Approach

Unlike Sora 2's reference image mode, Veo 3.1 supports uploading 2 images as the first and last frames of your video. The AI automatically generates the transition animation in between, creating a smooth transformation from A to B.

Core Advantages of Veo 3.1's First & Last Frame Feature

Veo 3.1 First & Last Frame API Example

import google.generativeai as genai
from google.genai import types

# Configure API (through apiyi.com proxy)
genai.configure(api_key="YOUR_API_KEY")

# Load first and last frame images
first_frame = genai.upload_file("start_scene.jpg")
last_frame = genai.upload_file("end_scene.jpg")

# Veo 3.1 first/last frame generation
response = genai.models.generate_videos(
    model="veo-3.1",
    prompt="Smooth scene transition, cinematic quality",
    image=first_frame,
    config=types.GenerateVideosConfig(
        last_frame=last_frame,
        duration_seconds=8
    )
)

Veo 3.1 Special Feature: Beyond first/last frame control, Veo 3.1 also supports up to 4 reference images for visual guidance, maintaining character and style consistency. This feature is only available in the standard Veo 3.1 version—it's not supported in the Fast version.

Sora 2 vs Veo 3 Image-to-Video Comparison

How to Choose? Scenario Decision Guide

Go with Sora 2 when:

• You've got a character or scene reference image and want the AI to get creative with it
• You need to maintain consistent brand visual style
• You'd like the AI to figure out the best composition and motion trajectories
• You're creating 12-second video content

Choose Veo 3.1 when:

• You know exactly what your start and end frames should look like
• You need to showcase product A→B transformations
• You want to create perfectly looping background animations
• You're working on scene transitions or morphing effects

FAQ

Summary

The core differences between Sora 2 and Veo 3's image-to-video capabilities:

1. Different number of images: Sora 2 supports 1 reference image, Veo 3.1 supports 2 first and last frames
2. Different image functions: Sora 2's reference image blends into the video style, Veo 3.1's first and last frames precisely control start and end points
3. Different use cases: Sora 2 is suitable for open-ended creation, Veo 3.1 is ideal for goal-oriented transition effects

Understanding the essential differences between these two mechanisms will help you choose the most appropriate API based on your specific needs and achieve better creative results.

We recommend accessing both Sora 2 and Veo 3 APIs through APIYI apiyi.com, which provides a unified interface and free testing credits for convenient comparison testing and flexible switching.

📚 References

⚠️ Link Format Note: All external links use the Resource Name: domain.com format for easy copying but aren't clickable, helping avoid SEO weight loss.

1. OpenAI Sora API Official Documentation: Complete Sora Video Generation Guide

   • Link: platform.openai.com/docs/guides/video-generation
   • Description: Learn about Sora 2's official parameters and usage for image-to-video generation

2. Google Veo 3.1 First & Last Frame Documentation: Vertex AI Video Generation Guide

   • Link: docs.cloud.google.com/vertex-ai/generative-ai/docs/video/generate-videos-from-first-and-last-frames
   • Description: Detailed guide on using Veo 3.1's first and last frame functionality

3. Sora 2 Prompting Guide: OpenAI Official Prompt Guide

   • Link: cookbook.openai.com/examples/sora/sora2_prompting_guide
   • Description: Learn how to write high-quality Sora 2 video prompts

4. Google Veo 3.1 Feature Breakdown: First/Last Frame and Reference Image Deep Dive

   • Link: getimg.ai/blog/google-veo-3-1-review
   • Description: In-depth look at Veo 3.1's new features and usage tips

Author: Technical Team
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