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LLM for Use CaseSummarisationGPT-5.5 vs Sora 2 Pro

GPT-5.5 vs Sora 2 Pro for Summarisation

Which AI model is better for summarisation? We compare GPT-5.5 and Sora 2 Pro on the criteria that matter most - with a clear verdict.

Why your summarisation LLM choice matters

Effective summarisation requires more than shortening text - it demands identifying what is genuinely important, preserving key nuance, and structuring the output for its intended use. For long documents, large context windows are essential: models that truncate input or hallucinate information they did not actually process are actively counterproductive.

Key evaluation criteria for summarisation

1Accuracy and completeness of key information
2Context window size for long document handling
3Structured output formats (bullets, sections)
4Reduction ratio without information loss

Side-by-Side Comparison

FeatureGPT-5.5WinnerSora 2 Pro
ProviderOpenAIOpenAI
Model Typetextvideo
Context Window1,000,000 tokens400,000 tokens
Input Cost
$5.00/ 1M tokens
N/A
Output Cost
$30.00/ 1M tokens
N/A
Top pick for Summarisation

Strengths for Summarisation

GPT-5.5

OpenAI

1. Strongest Agentic Coding Model

  • State-of-the-art on Terminal-Bench 2.0 (82.7%), Expert-SWE (73.1%), and SWE-Bench Pro (58.6%), outperforming GPT-5.4 on complex coding tasks.
  • Holds context across large systems, reasons through ambiguous failures, and carries changes through surrounding codebases with fewer tokens.

2. Higher Intelligence at GPT-5.4 Latency

  • Co-designed, trained, and served on NVIDIA GB200/GB300 NVL72 systems to match GPT-5.4 per-token latency while performing at a significantly higher level.
  • Uses fewer tokens to complete the same tasks, making it more efficient as well as more capable.

3. Powerful for Knowledge Work & Computer Use

  • Scores 84.9% on GDPval (44 occupations) and 78.7% on OSWorld-Verified for autonomous computer operation.
  • Excels at generating documents, spreadsheets, and reports; naturally moves across finding information, using tools, and checking output.

4. Scientific Research Co-Scientist

  • Leading performance on GeneBench, BixBench, and FrontierMath; helped discover a new proof about Ramsey numbers verified in Lean.
  • Strong enough to meaningfully accelerate progress at the frontiers of biomedical and mathematical research.

Sora 2 Pro

OpenAI

1. Highest-Performance Video Generation

  • Sora 2 Pro is the top-tier model in the Sora family, built for maximum detail, realism, and scene complexity.
  • Generates highly dynamic sequences with sophisticated motion, environment depth, and visual coherence.

2. Superior Synced-Audio Output

  • Produces audio that matches on-screen timing, actions, and emotional tone.
  • Ideal for storytelling, cinematic content, marketing assets, and creative production where audio-visual alignment is critical.

3. Enhanced Resolution Options

  • Supports two quality tiers:
    • Standard: 720 x 1280 (portrait), 1280 x 720 (landscape)
    • High resolution: 1024 x 1792 (portrait), 1792 x 1024 (landscape)
  • Higher tier is optimized for premium production workflows such as advertising, film pre-visualization, and design studios.

4. Deep Scene Understanding

  • Creates richly detailed environments, characters, and multi-object interactions.
  • Suitable for handling complex prompts requiring:
    • Perspective shifts
    • Camera motion
    • Atmospheric and lighting realism
    • Emotionally expressive scenes

5. Multi-Modal Input With Full Media Output

  • Accepts text and image inputs for narrative-to-video or image-to-video pipelines.
  • Outputs video and audio, providing a complete media asset without external editing tools.

6. Integrated Across Core API Endpoints

  • Available through:
    • Chat Completions
    • Responses
    • Realtime
    • Assistants
    • Videos endpoint
  • Enables integration in video agents, creative assistants, automated content generators, and interactive applications.

7. Consistent, Predictable Model Behavior

  • Stable snapshots help lock in output consistency for long, ongoing production workflows.
  • Ensures predictable rendering across iterative projects or episodic content creation.

8. Ideal Use Cases

  • High-end creative storytelling
  • Product commercials and brand videos
  • App or UX demos
  • Previs for films and games
  • Educational or explainer videos
  • Social media and high-resolution promotional content

Verdict: Best LLM for Summarisation

For summarisation tasks, GPT-5.5 edges ahead based on its performance profile and design priorities. It scores higher on accuracy and completeness of key information - the criterion that matters most for summarisation workflows.

That said, Sora 2 Pro remains a strong option. If reduction ratio without information loss is a higher priority than raw performance, or if your team is already using OpenAI's tooling, Sora 2 Pro can deliver strong results for summarisation workloads.

With Appaca, you can build summarisation apps powered by either model and switch between them at any time - no rebuild required. Test what actually performs best for your users before committing.

You know GPT-5.5 wins for summarisation. Now build with it.

Most teams spend days comparing models and hours copy-pasting prompts. With Appaca, you build a dedicated summarisation app - powered by GPT-5.5 - in minutes. No code, no re-prompting, runs on any device.

Free to start. Switch models any time. No rebuild required.

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Frequently asked questions

Is GPT-5.5 or Sora 2 Pro better for summarisation?

For summarisation tasks, GPT-5.5 has the edge based on its performance profile and design priorities. It ranks higher on accuracy and completeness of key information, which is the most important criterion for summarisation workflows. That said, both models can handle summarisation workloads - the best choice depends on your specific requirements and budget.

What are the key differences between GPT-5.5 and Sora 2 Pro for summarisation?

The main differences are in accuracy and completeness of key information, context window size for long document handling, structured output formats (bullets, sections). GPT-5.5 is developed by OpenAI and shares the same provider as Sora 2 Pro. Context window, pricing, and speed all differ - check the comparison table above for a side-by-side breakdown.

How much does it cost to use GPT-5.5 vs Sora 2 Pro?

Pricing varies by plan and volume. Check each provider's current API pricing for exact per-token costs for your summarisation use case.

Can I build a summarisation app with GPT-5.5 or Sora 2 Pro?

Yes. Both models can power summarisation applications. With Appaca, you can build a summarisation app using either GPT-5.5 or Sora 2 Pro - and switch between them at any time to find the model that performs best for your specific workflow, without rebuilding your product.

Which model should I choose if I care most about accuracy and completeness of key information?

GPT-5.5 is the stronger choice when accuracy and completeness of key information is your top priority. It ranks #3 overall for summarisation tasks. If cost or latency are constraints, Sora 2 Pro may still meet your needs at a lower cost.