GPT-5.6 Sol vs GPT-5.5
Compare pricing, context windows, and strengths for GPT-5.6 Sol by OpenAI and GPT-5.5 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 SolGPT-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-5.6 Sol vs GPT-5.5 at a glance
Specs and pricing side by side, from the Appaca AI models directory.
| Spec | GPT-5.6 Sol | GPT-5.5 |
|---|---|---|
| Provider | OpenAI | OpenAI |
| Model type | Text | Text |
| Context window | 1.05M tokens | 1M tokens |
| Input price | $5 / 1M tokens | $5 / 1M tokens |
| Output price | $30 / 1M tokens | $30 / 1M tokens |
| Status | Current | Superseded by GPT-5.6 Sol |
How GPT-5.6 Sol and GPT-5.5 differ
What the numbers mean in practice when choosing between GPT-5.6 Sol and GPT-5.5.
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Both models cost the same on input: $5 per million tokens.
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Context windows are close: GPT-5.6 Sol handles 1.05M tokens and GPT-5.5 handles 1M tokens.
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GPT-5.5 has been superseded by GPT-5.6 Sol - for new builds, consider the newer model first.
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.
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.
Use GPT-5.6 Sol or GPT-5.5 - or both
Appaca is the AI workspace for operators. Build internal tools and AI co-workers powered by GPT-5.6 Sol or GPT-5.5 - 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 GPT-5.5. No code, no API keys, no deployment.
Switch models without rebuilding
Start on GPT-5.6 Sol, test the same tool on GPT-5.5, 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 GPT-5.5 - connected to the tools you already use.
Related comparisons
See how GPT-5.6 Sol and GPT-5.5 stack up against other models in the directory.
FAQs
They cost the same overall: both charge $5 per million input tokens and $30 per million output tokens.
GPT-5.6 Sol has the larger context window at 1.05M tokens, compared to 1M tokens for GPT-5.5. 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 GPT-5.5, 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, GPT-5.5, 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 GPT-5.5
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.