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GPT-5 Nano vs GPT-4 Turbo

Compare pricing, context windows, and strengths for GPT-5 Nano by OpenAI and GPT-4 Turbo by OpenAI - and see how to put either to work in Appaca.

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GPT-5 Nano

The fastest and cheapest GPT-5 variant, ideal for summarization, classification, and lightweight tasks requiring high speed and low cost.

View GPT-5 Nano
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GPT-4 Turbo

Older high-intelligence GPT-4 generation model offering strong reasoning and image input support, now superseded by newer 4o-based models.

View GPT-4 Turbo

GPT-5 Nano vs GPT-4 Turbo at a glance

Specs and pricing side by side, from the Appaca AI models directory.

Spec GPT-5 Nano GPT-4 Turbo
Provider OpenAI OpenAI
Model type Text Text
Context window 400K tokens 128K tokens
Input price $0.05 / 1M tokens $10 / 1M tokens
Output price $0.4 / 1M tokens $30 / 1M tokens
Status Current Current
Key differences

How GPT-5 Nano and GPT-4 Turbo differ

What the numbers mean in practice when choosing between GPT-5 Nano and GPT-4 Turbo.

  • GPT-5 Nano is 100% cheaper on input tokens ($0.05 vs $10 per million), which adds up quickly in document-heavy workloads.

  • GPT-5 Nano is 99% cheaper on output tokens ($0.4 vs $30 per million) - the bigger factor for tools that generate long documents.

  • GPT-5 Nano's 400K tokens context window is roughly 3.1x larger than GPT-4 Turbo's 128K 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 Nano

1. Extremely fast performance

  • Fastest model in the GPT-5 family.
  • Great for real-time workflows, rapid responses, and high-throughput systems.

2. Most cost-efficient GPT-5 model

  • Lowest input and output token costs.
  • Suitable for large-scale or budget-sensitive applications.

3. Ideal for lightweight, well-scoped tasks

  • Excels at summarization, classification, text extraction, and simple logic tasks.
  • Best used when tasks are narrow and well-defined.

4. Multimodal input

  • Accepts text + image as input.
  • Outputs text only.

5. Broad tool support

  • Supports Web Search, File Search, Image Generation (as a tool), Code Interpreter, and MCP.
  • (Does not support Computer Use.)

GPT-4 Turbo

1. Strong reasoning for its generation

  • Next-gen version of GPT-4 designed to be cheaper and faster than the original.
  • Good for analytical tasks, structured writing, coding guidance, and multi-step reasoning.

2. Image input support

  • Accepts images and provides text-only outputs.
  • Useful for OCR, visual Q&A, document extraction, UI analysis, and design interpretation.

3. Stable performance

  • Predictable model behavior suitable for legacy systems still built on GPT-4.
  • Works reliably for established pipelines and enterprise workloads.

4. Large 128K context window

  • Handles long documents, multi-file inputs, or extended conversational sessions.
  • Allows complex prompt chaining and large instruction sets.

5. Broad endpoint compatibility

  • Works with Chat Completions, Responses API, Realtime API, Assistants, Batch, Fine-tuning, Embeddings, and more.
  • Supports streaming and function calling.

6. Good choice for cost-controlled GPT-4-class workloads

  • Although older, still useful for teams who want GPT-4-level reasoning without upgrading immediately.
  • A midpoint between legacy GPT-4 and modern GPT-4o/5.1 models.

7. Text-only output simplifies downstream use

  • Ensures deterministic outputs for applications that need reliable text generation.
  • Good for RAG, data pipelines, automation tools, and enterprise systems.

8. Recommended migration path

  • OpenAI now recommends using GPT-4o or GPT-5.1 for improved speed, cost, reasoning, and multimodal capability.
  • GPT-4 Turbo remains available for backward compatibility and stability.
Appaca

Use GPT-5 Nano or GPT-4 Turbo - or both

Appaca is the AI workspace for operators. Build internal tools and AI co-workers powered by GPT-5 Nano or GPT-4 Turbo - 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 Nano or GPT-4 Turbo. No code, no API keys, no deployment.

Switch models without rebuilding

Start on GPT-5 Nano, test the same tool on GPT-4 Turbo, 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 Nano or GPT-4 Turbo - connected to the tools you already use.

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FAQs

Is GPT-5 Nano cheaper than GPT-4 Turbo?

GPT-5 Nano is generally cheaper: $0.05 input / $0.4 output per million tokens, versus $10 / $30 for GPT-4 Turbo. Actual cost depends on how many tokens your workload reads and writes.

Which has the larger context window, GPT-5 Nano or GPT-4 Turbo?

GPT-5 Nano has the larger context window at 400K tokens, compared to 128K tokens for GPT-4 Turbo. A larger window means the model can consider more text at once - useful for long contracts, codebases, or months of records.

Should I use GPT-5 Nano or GPT-4 Turbo?

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 Nano, test the same tool on GPT-4 Turbo, and switch at any time without rebuilding anything.

Can I use GPT-5 Nano and GPT-4 Turbo without writing code?

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 Nano, GPT-4 Turbo, 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 Nano or GPT-4 Turbo

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.