Done comparing? Build a data analysis app powered by GPT-5.4.
Build with GPT-5.4 freeGPT-5.4 vs GPT-OSS 120B for Data Analysis
Which AI model is better for data analysis? We compare GPT-5.4 and GPT-OSS 120B 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
Side-by-Side Comparison
| Feature | GPT-5.4Winner | GPT-OSS 120B |
|---|---|---|
| Provider | OpenAI | OpenAI |
| Model Type | text | text |
| Context Window | 1,050,000 tokens | 131,072 tokens |
| Input Cost | $2.50/ 1M tokens | $0.00/ 1M tokens |
| Output Cost | $15.00/ 1M tokens | $0.00/ 1M tokens |
| Top pick for Data Analysis |
Strengths for Data Analysis
GPT-5.4
OpenAI1. Best Intelligence at Scale
- OpenAI positions GPT-5.4 as its frontier model for agentic, coding, and professional workflows.
- Built for complex professional work where stronger reasoning and higher answer quality matter.
2. Configurable Reasoning + Multimodal Input
- Supports configurable reasoning effort from none to xhigh, letting teams balance speed and depth.
- Accepts both text and image inputs while producing text output.
3. Massive Context for Long-Running Work
- 1.05M token context window supports very large codebases, documents, and multi-step workflows.
- Allows up to 128 k output tokens for long-form answers and larger generations.
4. Updated Knowledge & Broad Tool Support
- Knowledge cut-off of Aug 31 2025 keeps it current for newer frameworks and business context.
- Supports tools like web search, file search, code interpreter, hosted shell, computer use, and MCP in the Responses API.
GPT-OSS 120B
OpenAI1. Most powerful open-weight model
- 117B parameters (5.1B active) while fitting on a single H100 GPU.
- High reasoning quality compared to other open models.
2. Apache 2.0 license
- Fully permissive, no copyleft or patent restrictions.
- Safe for commercial products, research, and redistribution.
3. Configurable reasoning effort
- Supports adjustable reasoning: low, medium, high.
- Lets developers balance latency vs. depth.
4. Full chain-of-thought access
- Unlike closed commercial models, this exposes complete reasoning traces.
- Useful for debugging, auditing, safety research, and transparency.
5. Fine-tunable
- Fully supports parameter fine-tuning.
- Can be adapted to domain-specific workflows and proprietary datasets.
6. Agentic capabilities
- Built-in function calling.
- Native support for web browsing, Python execution, and structured outputs.
- Ideal for open-source agents, full-stack automation, and developer tooling.
7. Tooling ecosystem support
- Compatible with Chat Completions, Responses API, Assistants, Realtime, Batch, and Fine-tuning endpoints.
- Supports Image Generation, Code Interpreter (via Python runtime), and more.
8. Open-source availability
- Downloadable on HuggingFace for local or on-prem deployment.
- Supports full offline, private, or self-hosted usage.
9. Streaming + function calling support
- Real-time interactions.
- Strong for interactive agents, coding assistants, and UI-driven workflows.
Verdict: Best LLM for Data Analysis
For data analysis tasks, GPT-5.4 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, GPT-OSS 120B 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 OpenAI's tooling, GPT-OSS 120B 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-5.4 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-5.4 - in minutes. No code, no re-prompting, runs on any device.
Free to start. Switch models any time. No rebuild required.
Build a data analysis app with GPT-5.4 - freeFrequently asked questions
Is GPT-5.4 or GPT-OSS 120B better for data analysis?
For data analysis tasks, GPT-5.4 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-5.4 and GPT-OSS 120B 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-5.4 is developed by OpenAI and shares the same provider as GPT-OSS 120B. 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-5.4 vs GPT-OSS 120B?
GPT-OSS 120B is cheaper at $0.00/million input tokens, versus $2.50/million for GPT-5.4. 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-5.4 or GPT-OSS 120B?
Yes. Both models can power data analysis applications. With Appaca, you can build a data analysis app using either GPT-5.4 or GPT-OSS 120B - 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-5.4 is the stronger choice when accuracy of quantitative reasoning and calculations is your top priority. It ranks #4 overall for data analysis tasks. If cost or latency are constraints, GPT-OSS 120B may still meet your needs at a lower cost.