GPT-5.6 Sol vs GPT-4.1 Nano
Compare pricing, context windows, and strengths for GPT-5.6 Sol by OpenAI and GPT-4.1 Nano 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-4.1 Nano
Fastest and most cost-efficient GPT-4.1 model with strong instruction following, tool calling, and a 1M-token context window for lightweight, real-time tasks.
View GPT-4.1 NanoGPT-5.6 Sol vs GPT-4.1 Nano at a glance
Specs and pricing side by side, from the Appaca AI models directory.
| Spec | GPT-5.6 Sol | GPT-4.1 Nano |
|---|---|---|
| Provider | OpenAI | OpenAI |
| Model type | Text | Text |
| Context window | 1.05M tokens | 1.05M tokens |
| Input price | $5 / 1M tokens | $0.1 / 1M tokens |
| Output price | $30 / 1M tokens | $0.4 / 1M tokens |
| Status | Current | Superseded by GPT-5 Mini |
How GPT-5.6 Sol and GPT-4.1 Nano differ
What the numbers mean in practice when choosing between GPT-5.6 Sol and GPT-4.1 Nano.
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GPT-4.1 Nano is 98% cheaper on input tokens ($0.1 vs $5 per million), which adds up quickly in document-heavy workloads.
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GPT-4.1 Nano is 99% cheaper on output tokens ($0.4 vs $30 per million) - the bigger factor for tools that generate long documents.
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Context windows are close: GPT-5.6 Sol handles 1.05M tokens and GPT-4.1 Nano handles 1.05M tokens.
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GPT-4.1 Nano has been superseded by GPT-5 Mini - for new builds, consider the newer model first.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-4.1 Nano
1. Ultra-Fast, Low-Latency Performance
- The fastest model in the GPT-4.1 family, ideal for real-time interactions and high-throughput applications.
- Designed for scenarios where speed matters more than complex reasoning.
2. Most Cost-Efficient GPT-4.1 Variant
- Lowest price point among GPT-4.1 models.
- Enables large-scale deployments such as support bots, routing systems, and lightweight assistants without high compute costs.
3. Solid Instruction Following
- Consistent and reliable at following clear instructions.
- Well-suited for:
- Classification
- Simple reasoning
- Data extraction
- Content rewriting
- Chat-style responses
4. Strong Tool Calling Capabilities
- Built with robust support for:
- Function calling
- Structured outputs (e.g., JSON)
- Lightweight automation tasks
- Works well within multi-step agent workflows that rely on simple tools.
5. Basic Multimodal Input
- Supports text and image input.
- Useful for:
- Simple visual recognition
- Alt-text generation
- Reading graphics or screenshots
6. Text-Only Output
- Produces text only, ensuring:
- Clean structured outputs
- High reliability for downstream processing
- Ease of integration into backend systems
7. 1M-Token Context Window
- Supports up to 1,047,576 tokens, allowing:
- Long documents
- Multiple files
- Large prompt memory
- Reduces or eliminates the need for chunking and retrieval in many simple workflows.
8. Ideal Use Cases
- Customer support bots
- Routing and intent detection
- Simple agents and workflow automation
- Content cleanup and rewriting
- Basic Q&A, summaries, and extraction
9. Broad API Integration
- Available across major API endpoints:
- Chat Completions
- Responses
- Realtime
- Assistants
- Fine-tuning
- Supports predicted outputs for reliability and determinism.
Use GPT-5.6 Sol or GPT-4.1 Nano - or both
Appaca is the AI workspace for operators. Build internal tools and AI co-workers powered by GPT-5.6 Sol or GPT-4.1 Nano - 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-4.1 Nano. No code, no API keys, no deployment.
Switch models without rebuilding
Start on GPT-5.6 Sol, test the same tool on GPT-4.1 Nano, 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-4.1 Nano - connected to the tools you already use.
Related comparisons
See how GPT-5.6 Sol and GPT-4.1 Nano stack up against other models in the directory.
FAQs
GPT-4.1 Nano is generally cheaper: $0.1 input / $0.4 output per million tokens, versus $5 / $30 for GPT-5.6 Sol. 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 1.05M tokens for GPT-4.1 Nano. 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-4.1 Nano, 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-4.1 Nano, 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-4.1 Nano
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.