GPT-5.4 vs Claude 4.5 Opus

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. Maximum capability with more practical pricing

• Anthropic introduced Opus 4.5 as its most intelligent model, combining maximum capability with practical performance.
• It was positioned as the best model in the world for coding, agents, and computer use at launch, with pricing reduced to $5/M input and $25/M output.

2. Step-change gains for coding and advanced agent work

• Anthropic describes Opus 4.5 as state-of-the-art on real-world software engineering tests.
• It also improved everyday knowledge-work tasks like deep research, slides, and spreadsheets while staying strong on long-horizon agent workflows.

3. Better control over reasoning depth

• Opus 4.5 introduced the effort parameter, letting developers trade off response thoroughness against token efficiency.
• This made it easier to use one flagship model across both high-depth analysis and more cost-sensitive production workloads.

4. Stronger computer use and continuity

• Added enhanced computer use with a zoom action for inspecting detailed screen regions.
• Preserves prior thinking blocks across turns, helping the model maintain reasoning continuity in extended multi-step tasks.