1. Strongest Agentic Coding Model

• State-of-the-art on Terminal-Bench 2.0 (82.7%), Expert-SWE (73.1%), and SWE-Bench Pro (58.6%), outperforming GPT-5.4 on complex coding tasks.
• Holds context across large systems, reasons through ambiguous failures, and carries changes through surrounding codebases with fewer tokens.

2. Higher Intelligence at GPT-5.4 Latency

• Co-designed, trained, and served on NVIDIA GB200/GB300 NVL72 systems to match GPT-5.4 per-token latency while performing at a significantly higher level.
• Uses fewer tokens to complete the same tasks, making it more efficient as well as more capable.

3. Powerful for Knowledge Work & Computer Use

• Scores 84.9% on GDPval (44 occupations) and 78.7% on OSWorld-Verified for autonomous computer operation.
• Excels at generating documents, spreadsheets, and reports; naturally moves across finding information, using tools, and checking output.

4. Scientific Research Co-Scientist

• Leading performance on GeneBench, BixBench, and FrontierMath; helped discover a new proof about Ramsey numbers verified in Lean.
• Strong enough to meaningfully accelerate progress at the frontiers of biomedical and mathematical research.

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.