GPT-5.4 vs o1

1. Best Intelligence at Scale

• OpenAI positions GPT-5.4 as its frontier model for agentic, coding, and professional workflows.
• Built for complex professional work where stronger reasoning and higher answer quality matter.

2. Configurable Reasoning + Multimodal Input

• Supports configurable reasoning effort from none to xhigh, letting teams balance speed and depth.
• Accepts both text and image inputs while producing text output.

3. Massive Context for Long-Running Work

• 1.05M token context window supports very large codebases, documents, and multi-step workflows.
• Allows up to 128 k output tokens for long-form answers and larger generations.

4. Updated Knowledge & Broad Tool Support

• Knowledge cut-off of Aug 31 2025 keeps it current for newer frameworks and business context.
• Supports tools like web search, file search, code interpreter, hosted shell, computer use, and MCP in the Responses API.

1. Full-scale reasoning model

• Uses reinforcement learning to generate long internal chains of thought.
• Suitable for tasks requiring deep logic, multi-step planning, and rich analytical reasoning.

2. Strong performance across domains

• Excellent at math, science, coding, and structured analytical work.
• Handles multi-step workflows and complex problem-solving with high consistency.

3. High output capacity (100K tokens)

• Enables long, detailed explanations, large documents, and multi-part analyses.

4. Image-understanding capable

• Accepts text + image inputs for visual reasoning and mixed-modality tasks.
• Output is text only, optimized for clear explanations.

5. Advanced API compatibility

• Works with Chat Completions, Responses, Realtime, Assistants, and more.
• Supports streaming, function calling, and structured outputs.

6. Stable long-context performance

• 200K-token context window supports large files, multi-document analysis, and extended conversations.

7. Designed for correctness-oriented workloads

• Prioritizes rigorous reasoning over speed.
• Useful in auditing, verification, scientific thinking, policy analysis, and legal-style reasoning.

8. Powerful but expensive

• High token costs make it suitable for selective, mission-critical reasoning rather than high-volume usage.