GPT-4o vs Claude 4.6 Sonnet

1. High-intelligence, general-purpose model

• Strong reasoning, creativity, summarization, and problem-solving.
• Great balance of speed, accuracy, and cost.

2. Multimodal input support

• Accepts text + image inputs for visual reasoning, extraction, or description.
• Output is text only, making it predictable for production.

3. Excellent for structured and unstructured tasks

• Performs well on Q&A, writing, analysis, classification, chat, and planning.
• Supports Structured Outputs, making it suitable for deterministic workflows.

4. Strong tool-use capabilities

• Supports function calling, API orchestration, and tool-augmented workflows.
• Integrates well with assistants, batch operations, and automation pipelines.

5. Large context for complex tasks

• 128K context allows multi-document reasoning, multi-step conversations, and large input payloads.

6. Production-ready reliability

• Stable outputs, predictable behaviors, and broad modality coverage.
• Supported across all major API endpoints.

7. Lower latency than o-series reasoning models

• Faster responses due to no dedicated reasoning step.
• Ideal for interactive or near-real-time applications.

8. Fine-tuning and distillation supported

• Enables specialization for domain-specific tasks.
• Distillation helps create smaller, efficient custom models.

1. Most capable Sonnet model yet

• Anthropic describes Sonnet 4.6 as its most capable Sonnet model.
• It is a full upgrade across coding, computer use, long-context reasoning, agent planning, knowledge work, and design.

2. Stronger coding and professional task performance at Sonnet pricing

• Pricing remains at $3/M input and $15/M output, matching Sonnet 4.5.
• Anthropic says early-access developers strongly preferred it to Sonnet 4.5, and often even to Opus 4.5 for practical work.

3. Long-context, agent-friendly reasoning

• Supports up to a 1M token context window in beta.
• Anthropic reports better consistency, fewer false claims of success, fewer hallucinations, and more reliable follow-through on multi-step tasks.

4. Modern API controls for adaptive work

• Supports adaptive thinking and the effort parameter for balancing speed, cost, and depth.
• Gains dynamic filtering for web search and web fetch, helping agent workflows keep only relevant information in context.