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Also known as: Generative Pretrained Transformer 4
A large multimodal language model that accepts text and images and delivers advanced reasoning, alignment, and task performance.
DESCRIPTION
GPT-4 extends the Transformer architecture to multimodal inputs and improved alignment. It exhibits stronger reasoning, coding assistance, and instruction following than prior GPT versions. The model underpins many production applications via APIs, with features like function calling and system prompts. Safety mitigations reduce harmful or biased outputs, though hallucinations can persist. GPT-4 demonstrated competitive performance on standardized exams. It influenced research on evaluation, safety, and agentic tool use. Deployment typically involves guardrails, retrieval, and monitoring.
ALTERNATIVE DEFINITIONS
arXiv
GPT-4 is a large, multimodal model (accepting image and text inputs, emitting text outputs) that, while less capable than humans in many real-world scenarios, exhibits human-level performance on various professional and academic benchmarks.
Defines GPT-4 as multimodal and benchmark-competitive.
OpenAI
GPT-4 is OpenAI’s most advanced system, producing safer and more useful responses.
Focuses on safety and utility improvements.
RELATED TERMS
Transformer Model Multimodal Model RLHF Prompt Engineering Chain-of-Thought Assistant Prompt Function Calling Safety Alignment Retrieval-Augmented Generation Large Language Model
COMPETING TERMS
KNOWLEDGE AREAS
AI Data Science MLOps Platform & Tooling
TARGET AUDIENCE
AI Engineer Data Scientist MLOps Engineer AI Product Manager Chief Technology Officer
EXTERNAL SOURCES
- Wikipedia - GPT-4
- arXiv - GPT-4 technical report
- OpenAI - Official GPT-4 overview
- arXiv - Sparks of AGI analysis
TOP QUESTIONS
What makes GPT-4 different from GPT-3?
GPT-4 is multimodal, shows stronger reasoning, and includes improved alignment and safety mitigations. It also offers features like function calling and longer context options.
Category: Differences
How is GPT-4 commonly deployed in production?
Through hosted APIs with retrieval augmentation, guardrails, prompt templates, and monitoring for cost, latency, and drift.
Category: Deployment
What are the risks of using GPT-4?
Residual hallucinations, prompt injection, data leakage, and misuse risks require guardrails, input validation, and policy enforcement.
Category: Risk
How does GPT-4 support tool use and function calling?
Developers register functions; the model emits structured arguments for selected functions, enabling reliable API calls and integrations.
Category: Capabilities
Why is GPT-4 significant for enterprise applications?
Its accuracy, safety features, and ecosystem support make it suitable for workflows like support automation, coding, and analytics copilots.
Category: Relevancy
What are key evaluation practices for GPT-4?
Use task-specific benchmarks, human red-teaming, and production telemetry for quality, safety, and robustness assessments.
Category: Evaluation
What are notable alternatives to GPT-4?
Gemini and Claude are major competitors, with varying strengths in multimodality, context length, and tool use.
Category: Alternatives
How does GPT-4 handle images?
It accepts images as inputs, enabling tasks like captioning, OCR, and chart interpretation, returning text outputs.
Category: Capabilities
Where to start learning about GPT-4?
Read the technical report, experiment with API examples, and study prompt engineering and safety guidelines.
Category: GettingStarted