o1 vs o1-pro
Compare pricing, context windows, and strengths for o1 by OpenAI and o1-pro by OpenAI - and see how to put either to work in Appaca.
o1
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 o1o1-pro
A high-compute version of the o1 reasoning model, trained with reinforcement learning to think before answering and produce consistently stronger multi-step reasoning across math, science, coding, and analysis tasks.
View o1-proo1 vs o1-pro at a glance
Specs and pricing side by side, from the Appaca AI models directory.
| Spec | o1 | o1-pro |
|---|---|---|
| Provider | OpenAI | OpenAI |
| Model type | Text | Text |
| Context window | 200K tokens | 200K tokens |
| Input price | $15 / 1M tokens | $150 / 1M tokens |
| Output price | $60 / 1M tokens | $600 / 1M tokens |
| Status | Current | Current |
How o1 and o1-pro differ
What the numbers mean in practice when choosing between o1 and o1-pro.
-
o1 is 90% cheaper on input tokens ($15 vs $150 per million), which adds up quickly in document-heavy workloads.
-
o1 is 90% cheaper on output tokens ($60 vs $600 per million) - the bigger factor for tools that generate long documents.
-
Both models offer the same 200K tokens context window.
Strengths side by side
Where each model shines, according to benchmarks and provider positioning.
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.
o1-pro
1. Maximum-compute o-series model
- Uses significantly more compute per query compared to o1.
- Produces deeper, more reliable reasoning chains.
- Best suited for high-stakes tasks that need correctness over speed.
2. Trained with reinforcement learning for deliberate thinking
- Explicit "think-before-answer" architecture.
- Excels at complex reasoning requiring multi-step analysis.
3. Very strong at math, science, coding, and technical proofs
- Handles long derivations, algorithm design, and difficult logic problems.
- Produces structured and explainable reasoning trails.
4. Great for multi-turn reasoning workflows
- Responses API optimized: can think over multiple internal turns before responding.
- Ideal for agentic reasoning pipelines.
5. Large context window
- 200,000-token context for large documents, multi-file review, and long reasoning traces.
6. Multimodal input (text + image)
- Can analyze images for mathematical diagrams, charts, handwritten content, UI layouts, etc.
- Output is text only.
7. Consistency, reliability, and depth
- Designed for situations where accuracy matters more than latency or cost.
- Strong error-checking and self-correction abilities.
Use o1 or o1-pro - or both
Appaca is the AI workspace for operators. Build internal tools and AI co-workers powered by o1 or o1-pro - 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 o1 or o1-pro. No code, no API keys, no deployment.
Switch models without rebuilding
Start on o1, test the same tool on o1-pro, 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 o1 or o1-pro - connected to the tools you already use.
Related comparisons
See how o1 and o1-pro stack up against other models in the directory.
FAQs
o1 is generally cheaper: $15 input / $60 output per million tokens, versus $150 / $600 for o1-pro. Actual cost depends on how many tokens your workload reads and writes.
They are equal: both o1 and o1-pro support a 200K tokens context window.
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 o1, test the same tool on o1-pro, 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 o1, o1-pro, 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 o1 or o1-pro
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.