GPT-5.5 vs o1
Compare pricing, context windows, and strengths for GPT-5.5 by OpenAI and o1 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-5.5o1
A full-size o-series reasoning model trained with RL to think before answering, producing strong multi-step reasoning across math, code, and analysis tasks.
View o1GPT-5.5 vs o1 at a glance
Specs and pricing side by side, from the Appaca AI models directory.
| Spec | GPT-5.5 | o1 |
|---|---|---|
| Provider | OpenAI | OpenAI |
| Model type | Text | Text |
| Context window | 1M tokens | 200K tokens |
| Input price | $5 / 1M tokens | $15 / 1M tokens |
| Output price | $30 / 1M tokens | $60 / 1M tokens |
| Status | Current | Current |
How GPT-5.5 and o1 differ
What the numbers mean in practice when choosing between GPT-5.5 and o1.
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GPT-5.5 is 67% cheaper on input tokens ($5 vs $15 per million), which adds up quickly in document-heavy workloads.
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GPT-5.5 is 50% cheaper on output tokens ($30 vs $60 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 5x larger than o1's 200K 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.
o1
1. Full-scale reasoning model
- Uses reinforcement learning to generate long internal chains of thought.
- Suitable for tasks requiring deep logic, multi-step planning, and rich analytical reasoning.
2. Strong performance across domains
- Excellent at math, science, coding, and structured analytical work.
- Handles multi-step workflows and complex problem-solving with high consistency.
3. High output capacity (100K tokens)
- Enables long, detailed explanations, large documents, and multi-part analyses.
4. Image-understanding capable
- Accepts text + image inputs for visual reasoning and mixed-modality tasks.
- Output is text only, optimized for clear explanations.
5. Advanced API compatibility
- Works with Chat Completions, Responses, Realtime, Assistants, and more.
- Supports streaming, function calling, and structured outputs.
6. Stable long-context performance
- 200K-token context window supports large files, multi-document analysis, and extended conversations.
7. Designed for correctness-oriented workloads
- Prioritizes rigorous reasoning over speed.
- Useful in auditing, verification, scientific thinking, policy analysis, and legal-style reasoning.
8. Powerful but expensive
- High token costs make it suitable for selective, mission-critical reasoning rather than high-volume usage.
Use GPT-5.5 or o1 - or both
Appaca is the AI workspace for operators. Build internal tools and AI co-workers powered by GPT-5.5 or o1 - 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 o1. No code, no API keys, no deployment.
Switch models without rebuilding
Start on GPT-5.5, test the same tool on o1, 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 o1 - connected to the tools you already use.
Related comparisons
See how GPT-5.5 and o1 stack up against other models in the directory.
FAQs
GPT-5.5 is generally cheaper: $5 input / $30 output per million tokens, versus $15 / $60 for o1. 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 200K tokens for o1. 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 o1, 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, o1, 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 o1
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.