Sora 2 vs GPT-3.5 Turbo

1. Advanced Video Generation Capability

• Produces richly detailed, cinematic video clips from simple text or image prompts.
• Handles complex scenes, motion, lighting, environments, and multi-object interactions with high fidelity.

2. Synced Audio Generation

• Generates audio that aligns with the timing, actions, and mood of the video.
• Useful for creating complete media outputs without requiring external sound design.

3. Multi-Modal Input, Multi-Media Output

• Accepts text and image inputs, enabling:
  • Storyboard-to-video workflows
  • Image-to-video transformations
  • Concept illustrations expanded into full scenes
• Outputs video and audio, making it ideal for end-to-end content creation.

4. Resolution-Optimized Performance

• Provides high-quality generation at:
  • Portrait: 720 x 1280
  • Landscape: 1280 x 720
• Optimized for common mobile and web video formats used in social media, ads, and creative production.

5. Powerful Media Understanding

• Interprets natural language with strong scene comprehension.
• Capable of rendering realistic movement, physics, emotions, and atmosphere.
• Suitable for:
  • Marketing videos
  • Short films and creative storytelling
  • Product demos and conceptual visualizations

6. Integrated Across Major API Endpoints

• Supported in Chat Completions, Responses, Realtime, Assistants, and Videos endpoints.
• Makes it easy to integrate into agent workflows or interactive production pipelines.

7. Consistent Model Behavior via Snapshots

• Offers stable snapshots to lock model performance across long-term projects.
• Ensures reproducibility for content pipelines, asset libraries, and enterprise workflows.

8. Ideal Use Cases

• Storyboarding → full-scene generation
• Product or app demos visualized from text
• Educational and explainer videos
• Social media content creation
• Creative ideation and prototyping

1. Extremely low-cost text model

• One of the cheapest legacy models available.
• Suitable for very high-volume workloads with simple requirements.

2. Good for lightweight NLP tasks

• Classification, summarization, rewriting, paraphrasing, intent detection.
• Works for simple logic tasks and short reasoning sequences.

3. Works well for basic chatbots

• Optimized for Chat Completions API, originally powering early ChatGPT use cases.
• Good for rule-based or templated conversation flows.

4. Stable and predictable outputs

• Legacy behavior makes it suitable for systems built years ago that rely on its quirks.
• Good for backward compatibility or long-term enterprise pipelines.

5. Supports fine-tuning

• Useful for teams maintaining older fine-tuned GPT-3.5 models.
• Allows domain-specific compression of older datasets.

6. Limited capabilities compared to newer models

• No vision, no audio, no streaming, and no function calling.
• Much weaker reasoning and correctness vs GPT-4o mini or GPT-5.1.

7. Small context window (16K)

• Limited for multi-document tasks or long conversations.
• Best used for short, simple prompts or structured tasks.

8. Recommended migration path

• OpenAI explicitly recommends using GPT-4o mini instead.
• 4o mini is cheaper, smarter, faster, multimodal, and far more capable.