GPT-5.5 vs GPT-4o
Compare pricing, context windows, and strengths for GPT-5.5 by OpenAI and GPT-4o by OpenAI - and see how to put either to work in Appaca.
GPT-5.5
OpenAI's smartest and most capable model yet for agentic coding, knowledge work, and computer use, delivering a new class of intelligence at GPT-5.4 latency.
View GPT-5.5GPT-4o
A versatile, high-intelligence flagship GPT model that handles text and image inputs and produces fast, high-quality text outputs for a wide range of tasks.
View GPT-4oGPT-5.5 vs GPT-4o at a glance
Specs and pricing side by side, from the Appaca AI models directory.
| Spec | GPT-5.5 | GPT-4o |
|---|---|---|
| Provider | OpenAI | OpenAI |
| Model type | Text | Text |
| Context window | 1M tokens | 128K tokens |
| Input price | $5 / 1M tokens | $2.5 / 1M tokens |
| Output price | $30 / 1M tokens | $10 / 1M tokens |
| Status | Current | Current |
How GPT-5.5 and GPT-4o differ
What the numbers mean in practice when choosing between GPT-5.5 and GPT-4o.
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GPT-4o is 50% cheaper on input tokens ($2.5 vs $5 per million), which adds up quickly in document-heavy workloads.
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GPT-4o is 67% cheaper on output tokens ($10 vs $30 per million) - the bigger factor for tools that generate long documents.
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GPT-5.5's 1M tokens context window is roughly 7.8x larger than GPT-4o's 128K tokens, so it can work across bigger codebases, contracts, or archives in one pass.
Strengths side by side
Where each model shines, according to benchmarks and provider positioning.
GPT-5.5
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.
GPT-4o
1. High-intelligence, general-purpose model
- Strong reasoning, creativity, summarization, and problem-solving.
- Great balance of speed, accuracy, and cost.
2. Multimodal input support
- Accepts text + image inputs for visual reasoning, extraction, or description.
- Output is text only, making it predictable for production.
3. Excellent for structured and unstructured tasks
- Performs well on Q&A, writing, analysis, classification, chat, and planning.
- Supports Structured Outputs, making it suitable for deterministic workflows.
4. Strong tool-use capabilities
- Supports function calling, API orchestration, and tool-augmented workflows.
- Integrates well with assistants, batch operations, and automation pipelines.
5. Large context for complex tasks
- 128K context allows multi-document reasoning, multi-step conversations, and large input payloads.
6. Production-ready reliability
- Stable outputs, predictable behaviors, and broad modality coverage.
- Supported across all major API endpoints.
7. Lower latency than o-series reasoning models
- Faster responses due to no dedicated reasoning step.
- Ideal for interactive or near-real-time applications.
8. Fine-tuning and distillation supported
- Enables specialization for domain-specific tasks.
- Distillation helps create smaller, efficient custom models.
Use GPT-5.5 or GPT-4o - or both
Appaca is the AI workspace for operators. Build internal tools and AI co-workers powered by GPT-5.5 or GPT-4o - connected to your real data and ready for your whole team. No code, no deployment.
Describe it, and it's built
Tell the Appaca agent the internal tool you need and it builds a working app powered by GPT-5.5 or GPT-4o. No code, no API keys, no deployment.
Switch models without rebuilding
Start on GPT-5.5, test the same tool on GPT-4o, and keep whichever performs better - the rest of your app stays exactly as it is.
Automated for the whole team
Schedule tools to run on autopilot - daily digests, weekly reports, real-time triggers - and share them with your whole team from one workspace.
Describe it, and it's built
Tell the Appaca agent what your team needs and it builds a working app powered by GPT-5.5 or GPT-4o - connected to the tools you already use.
Related comparisons
See how GPT-5.5 and GPT-4o stack up against other models in the directory.
FAQs
GPT-4o is generally cheaper: $2.5 input / $10 output per million tokens, versus $5 / $30 for GPT-5.5. Actual cost depends on how many tokens your workload reads and writes.
GPT-5.5 has the larger context window at 1M tokens, compared to 128K tokens for GPT-4o. A larger window means the model can consider more text at once - useful for long contracts, codebases, or months of records.
It depends on the job. Compare the pricing, context window, and strengths above against your workload - and remember the choice isn't permanent. In Appaca you can build a tool on GPT-5.5, test the same tool on GPT-4o, and switch at any time without rebuilding anything.
Yes. Appaca is a no-code AI workspace: describe the internal tool your team needs and the Appaca agent builds it as a working app powered by GPT-5.5, GPT-4o, or any other model in the directory - with a built-in database, team access, and integrations. No API keys to wire up and nothing to deploy.
Build AI tools with GPT-5.5 or GPT-4o
Describe the tool your team needs and get a working app powered by the model you choose - with a built-in database, team access, and integrations. No code, no deployment.