GPT-4.1 vs Claude 4.5 Opus

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.

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.