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.

1. State-of-the-art reasoning

• Top performance across academic reasoning, scientific knowledge, math, and complex problem-solving.
• Excels at long-horizon, multi-step workflows and deep logical interpretation.

2. World-leading multimodal capabilities

• Natively understands text, images, videos, audio, and code.
• Ranked highest on benchmarks like MMMU-Pro, Video-MMMU, ScreenSpot-Pro.

3. Exceptional coding + agentic workflows

• Strong in competitive coding and real-world agentic tasks (SWE-Bench Verified, Terminal-Bench, LiveCodeBench).
• Improved tool calling, planning, and execution for autonomous or semi-autonomous agents.

4. Powerful for long-context tasks

• Effective at 128K-1M context windows with high retrieval accuracy.
• Ideal for document-heavy workflows, research, analysis, multi-file coding, and multi-document reasoning.

5. Strong information synthesis and interpretation

• Outperforms peers in chart reasoning, OCR, structured extraction, and screen understanding.
• Excellent at combining multimodal inputs into coherent, concise answers.

6. High reliability for enterprise tasks

• Benchmarks show superior factuality, grounding, and parametric knowledge.
• Strong multilingual accuracy and global commonsense performance.

7. Optimized for production agents

• Designed for complex multi-step planning, simultaneous task execution, and improved consistency.
• Works across coding, research, creative workflows, UI generation, and data-heavy applications.