LLM ComparisonGPT-5 ProClaude 4.6 Opus

GPT-5 Pro vs Claude 4.6 Opus

Compare GPT-5 Pro and Claude 4.6 Opus. Build AI products powered by either model on Appaca.

Model Comparison

FeatureGPT-5 ProClaude 4.6 Opus
ProviderOpenAIAnthropic
Model Typetexttext
Context Window400,000 tokens1,000,000 tokens
Input Cost
$15.00/ 1M tokens
$5.00/ 1M tokens
Output Cost
$120.00/ 1M tokens
$25.00/ 1M tokens

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Strengths & Best Use Cases

GPT-5 Pro

OpenAI

1. Highest reasoning quality in the GPT-5 family

  • Uses significantly more compute to "think harder" before responding.
  • Designed for the toughest reasoning tasks where answer quality matters more than speed.
  • Produces more precise, reliable, and detailed outputs than standard GPT-5.

2. Advanced multi-turn reasoning via Responses API

  • Available only in the Responses API to support:
    • Multi-turn internal model interactions before returning a reply.
    • Advanced control patterns (e.g., background mode for long-running jobs).
  • Ideal for complex workflows, deep planning, and multi-step analysis.

3. Configured for maximum effort by default

  • Always runs with reasoning.effort: 'high' (no lower-effort mode).
  • Prioritizes depth and correctness over latency and cost.

4. Multimodal input

  • Accepts text + image as input.
  • Outputs text, with strong instruction-following and analysis capabilities.

5. Tooling and ecosystem integration

  • Supports Web Search, File Search, and Image Generation (as tools).
  • Supports MCP and other Responses API tooling patterns.
  • Does not support Code Interpreter and does not support Computer Use, keeping focus on pure reasoning + tools.

Claude 4.6 Opus

Anthropic

1. Anthropic's top model for coding and agents

  • Anthropic positions Opus 4.6 as its most intelligent model for building agents and coding.
  • It builds on Opus 4.5 with higher reliability and precision for professional software engineering, complex agentic workflows, and high-stakes enterprise tasks.

2. Strong frontier performance on real agent benchmarks

  • Anthropic reports state-of-the-art results across coding and agentic evaluations.
  • Public benchmark highlights include 65.4% on Terminal-Bench 2.0, 72.7% on OSWorld, and 90.2% on BigLaw Bench.

3. Best fit for long-horizon, high-context work

  • Supports up to a 1M token context window in beta and up to 128K output tokens.
  • Designed for long-running tasks that need sustained planning, careful debugging, code review, and strong context retention.

4. Advanced reasoning controls and workflow support

  • Supports adaptive thinking and the effort parameter, including the new max effort level.
  • Anthropic also introduced fast mode, compaction, and dynamic filtering with web search and web fetch for Opus 4.6-era agent workflows.

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