GPT-4 Turbo Vision
A variant of GPT-4 with vision capabilities, processing both text and image inputs.
OpenAI Text and image understanding with large context
GPT-4 Turbo Vision is a multimodal language model developed by OpenAI that accepts both text and image inputs, allowing it to analyze visual content and answer questions about it. It is built on GPT-4 Turbo and extends the traditional text-only language model paradigm by incorporating vision capabilities, with a context window of 128,000 tokens. The model's training data has a cutoff of December 2023.
GPT-4 Turbo Vision is well suited for tasks that require reasoning over images alongside text, such as document analysis, visual question answering, interpreting diagrams, and describing image content. The large context window allows users to include substantial amounts of text alongside image inputs in a single request. It is available through OpenAI's API and is accessible on MindStudio without requiring separate API key management.
What GPT-4 Turbo Vision supports
Image Understanding
Accepts image inputs alongside text prompts and answers questions about visual content, including diagrams, photos, and documents.
Large Context Window
Supports up to 128,000 tokens per request, enabling long documents or multiple images to be included in a single prompt.
Fast Inference
Tagged as very fast, making it suitable for latency-sensitive applications that also require vision or long-context processing.
Visual Question Answering
Responds to natural language questions about image content, supporting use cases like chart interpretation and scene description.
Multimodal Reasoning
Combines textual and visual information within a single context to perform reasoning tasks that span both modalities.
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Get Started FreeBenchmark scores
Scores represent accuracy — the percentage of questions answered correctly on each test.
| Benchmark | What it tests | Score |
|---|---|---|
| MMLU-Pro | Expert knowledge across 14 academic disciplines | 69.4% |
| MATH-500 | Undergraduate and competition-level math problems | 73.7% |
| AIME 2024 | American math olympiad problems | 15.0% |
| LiveCodeBench | Real-world coding tasks from recent competitions | 29.1% |
| HLE | Questions that challenge frontier models across many domains | 3.3% |
| SciCode | Scientific research coding and numerical methods | 31.9% |
Common questions about GPT-4 Turbo Vision
What is the context window size for GPT-4 Turbo Vision?
GPT-4 Turbo Vision supports a context window of 128,000 tokens, allowing large amounts of text and image data to be included in a single request.
What types of inputs does GPT-4 Turbo Vision accept?
The model accepts both text and image inputs, enabling it to process visual content alongside natural language prompts.
What is the training data cutoff for GPT-4 Turbo Vision?
The model's training data has a cutoff of December 2023, meaning it does not have knowledge of events occurring after that date.
Who publishes GPT-4 Turbo Vision?
GPT-4 Turbo Vision is published by OpenAI and is accessible via the OpenAI API as well as through platforms like MindStudio.
What kinds of tasks is GPT-4 Turbo Vision best suited for?
It is well suited for tasks requiring visual understanding combined with language reasoning, such as visual question answering, document analysis, diagram interpretation, and image description.
Parameters & options
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