GPT-4 Turbo was OpenAI's high-capability flagship when released, extending GPT-4 with a 128K token context window, vision input support, and improved instruction-following at lower cost than the original GPT-4. It was positioned as the production workhorse for applications needing long-document analysis, multimodal understanding, and reliable structured output.
The model accepts image inputs alongside text, enabling document parsing, chart understanding, and screenshot analysis. Its 128K context makes it practical for large codebase review, lengthy legal documents, or multi-document synthesis. While newer models have since superseded it in raw capability, GPT-4 Turbo remains a well-understood, extensively deployed model with broad ecosystem support.
Key Features
128K token context window for long-document and multi-document tasks
Vision input — understands images, screenshots, diagrams, and charts
Strong structured output generation including JSON mode
Function calling and tool use for agentic pipeline integration
Improved instruction-following over original GPT-4
Broad language support including low-resource languages
Ideal Use Cases
Long legal, financial, or technical document analysis and summarization
Multimodal assistants that interpret screenshots or uploaded images
Large codebase review and code-level explanation across many files
Complex RAG pipelines that benefit from large context capacity
Enterprise chatbots requiring vision support and reliable tool calling
Example Prompts for GPT-4 Turbo
Technical Specifications
| Provider | OpenAI |
| Category | Text |
| Modality | Text -> Text |
| Context Window | 128K tokens |
| Training Cutoff | April 2023 |
Frequently Asked Questions
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