GPT-5.5 vs GPT-4.1

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. Smartest non-reasoning model

• Highest intelligence among models without a reasoning step.
• Great for tasks where speed + accuracy matter without deep chain-of-thought.

2. Excellent instruction following

• Very strong at structured tasks, formatting, and precise execution.
• Ideal for productized workflows and deterministic outputs.

3. Reliable tool calling

• Works smoothly with Web Search, File Search, Image Generation, and Code Interpreter.
• Supports MCP and advanced tool-enabled API flows.

4. Large 1M-token context window

• Allows extremely long conversations, large documents, and multi-file use cases.
• Handles context-heavy tasks without requiring chunking.

5. Low latency (no reasoning step)

• Faster responses than GPT-5 family when reasoning mode isn't required.
• More predictable timing for production use.

6. Multimodal input

• Accepts text + image.
• Output is text only.

7. Supports fine-tuning

• Can be fine-tuned for specialized tasks.
• Also supports distillation for smaller custom models.