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LLM for Use CaseData AnalysisGPT-5.5 vs Claude 4.5 Opus

GPT-5.5 vs Claude 4.5 Opus for Data Analysis

Which AI model is better for data analysis? We compare GPT-5.5 and Claude 4.5 Opus on the criteria that matter most - with a clear verdict.

Why your data analysis LLM choice matters

Data analysis LLMs must reason correctly about numbers, generate accurate and executable code, and translate raw data into clear, actionable narrative. Unlike writing errors that are easy to spot, quantitative mistakes can go undetected - making model reliability and confidence calibration especially critical for data workflows.

Key evaluation criteria for data analysis

1Accuracy of quantitative reasoning and calculations
2Quality of SQL and Python code generation
3Ability to interpret charts and structured data
4Clear, concise data-driven narrative generation

Side-by-Side Comparison

FeatureGPT-5.5WinnerClaude 4.5 Opus
ProviderOpenAIAnthropic
Model Typetexttext
Context Window1,000,000 tokens200,000 tokens
Input Cost
$5.00/ 1M tokens
$5.00/ 1M tokens
Output Cost
$30.00/ 1M tokens
$25.00/ 1M tokens
Top pick for Data Analysis

Strengths for Data Analysis

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.

Claude 4.5 Opus

Anthropic

1. Maximum capability with more practical pricing

  • Anthropic introduced Opus 4.5 as its most intelligent model, combining maximum capability with practical performance.
  • It was positioned as the best model in the world for coding, agents, and computer use at launch, with pricing reduced to $5/M input and $25/M output.

2. Step-change gains for coding and advanced agent work

  • Anthropic describes Opus 4.5 as state-of-the-art on real-world software engineering tests.
  • It also improved everyday knowledge-work tasks like deep research, slides, and spreadsheets while staying strong on long-horizon agent workflows.

3. Better control over reasoning depth

  • Opus 4.5 introduced the effort parameter, letting developers trade off response thoroughness against token efficiency.
  • This made it easier to use one flagship model across both high-depth analysis and more cost-sensitive production workloads.

4. Stronger computer use and continuity

  • Added enhanced computer use with a zoom action for inspecting detailed screen regions.
  • Preserves prior thinking blocks across turns, helping the model maintain reasoning continuity in extended multi-step tasks.

Verdict: Best LLM for Data Analysis

For data analysis tasks, GPT-5.5 edges ahead based on its performance profile and design priorities. It scores higher on accuracy of quantitative reasoning and calculations - the criterion that matters most for data analysis workflows.

That said, Claude 4.5 Opus remains a strong option. If clear, concise data-driven narrative generation is a higher priority than raw performance, or if your team is already using Anthropic's tooling, Claude 4.5 Opus can deliver strong results for data analysis workloads.

With Appaca, you can build data analysis 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 data analysis. Now build with it.

Most teams spend days comparing models and hours copy-pasting prompts. With Appaca, you build a dedicated data analysis 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 Claude 4.5 Opus better for data analysis?

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

What are the key differences between GPT-5.5 and Claude 4.5 Opus for data analysis?

The main differences are in accuracy of quantitative reasoning and calculations, quality of sql and python code generation, ability to interpret charts and structured data. GPT-5.5 is developed by OpenAI and comes from a different provider than Claude 4.5 Opus. 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 Claude 4.5 Opus?

Claude 4.5 Opus is cheaper at $5.00/million input tokens, versus $5.00/million for GPT-5.5. For data analysis workloads, the total cost difference depends on your average prompt length and volume.

Can I build a data analysis app with GPT-5.5 or Claude 4.5 Opus?

Yes. Both models can power data analysis applications. With Appaca, you can build a data analysis app using either GPT-5.5 or Claude 4.5 Opus - 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 of quantitative reasoning and calculations?

GPT-5.5 is the stronger choice when accuracy of quantitative reasoning and calculations is your top priority. It ranks #1 overall for data analysis tasks. If cost or latency are constraints, Claude 4.5 Opus may still meet your needs at a lower cost.