GPT-5.6 Sol vs o1
Compare pricing, context windows, and strengths for GPT-5.6 Sol by OpenAI and o1 by OpenAI - and see how to put either to work in Appaca.
GPT-5.6 Sol
OpenAI's flagship model for complex professional work, combining frontier reasoning, coding, computer use, and long-horizon agentic performance with greater token efficiency.
View GPT-5.6 Solo1
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-5.6 Sol vs o1 at a glance
Specs and pricing side by side, from the Appaca AI models directory.
| Spec | GPT-5.6 Sol | o1 |
|---|---|---|
| Provider | OpenAI | OpenAI |
| Model type | Text | Text |
| Context window | 1.05M tokens | 200K tokens |
| Input price | $5 / 1M tokens | $15 / 1M tokens |
| Output price | $30 / 1M tokens | $60 / 1M tokens |
| Status | Current | Current |
How GPT-5.6 Sol and o1 differ
What the numbers mean in practice when choosing between GPT-5.6 Sol and o1.
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GPT-5.6 Sol is 67% cheaper on input tokens ($5 vs $15 per million), which adds up quickly in document-heavy workloads.
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GPT-5.6 Sol 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-5.6 Sol's 1.05M tokens context window is roughly 5.3x 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-5.6 Sol
1. Frontier Coding & Agentic Performance
- Scores 88.8% on Terminal-Bench 2.1 and 72.7% on DeepSWE v1.1, with stronger performance across complex terminal workflows and long-horizon engineering.
- Programmatic Tool Calling can coordinate tools, process intermediate results, and adapt workflows with fewer model round trips.
2. Maximum Capability on Demand
- Adds max reasoning effort for difficult tasks that benefit from deeper exploration, checking, and revision.
- Multi-agent ultra coordinates parallel agents for demanding work, reaching 91.9% on Terminal-Bench 2.1 and 92.2% on BrowseComp in OpenAI's evaluations.
3. Strong Computer Use, Design & Knowledge Work
- Scores 62.6% on OSWorld 2.0 and 90.4% on BrowseComp in standard mode.
- Produces more polished interfaces, presentations, documents, and spreadsheets while following reference formats more accurately.
4. Long Context & Broad Tool Support
- Supports a 1.05M-token context window, up to 128K output tokens, and text plus image input.
- Works with web search, file search, image generation, code interpreter, hosted shell, computer use, MCP, and other Responses API tools.
5. Stronger Science, Cybersecurity & Safeguards
- Improves scientific and defensive cybersecurity performance, including 28.7% on GeneBench Pro and 73.5% on ExploitBench.
- Uses layered safeguards, real-time checks, monitoring, and access controls for higher-risk capabilities.
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-5.6 Sol or o1 - or both
Appaca is the AI workspace for operators. Build internal tools and AI co-workers powered by GPT-5.6 Sol 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-5.6 Sol or o1. No code, no API keys, no deployment.
Switch models without rebuilding
Start on GPT-5.6 Sol, 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-5.6 Sol or o1 - connected to the tools you already use.
Related comparisons
See how GPT-5.6 Sol and o1 stack up against other models in the directory.
FAQs
GPT-5.6 Sol 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-5.6 Sol has the larger context window at 1.05M 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-5.6 Sol, 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-5.6 Sol, 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-5.6 Sol 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.