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LLM ComparisonGPT-5 Proo1

GPT-5 Pro vs o1

Compare GPT-5 Pro and o1. Build AI products powered by either model on Appaca.

Model Comparison

FeatureGPT-5 Proo1
ProviderOpenAIOpenAI
Model Typetexttext
Context Window400,000 tokens200,000 tokens
Input Cost
$15.00/ 1M tokens
$15.00/ 1M tokens
Output Cost
$120.00/ 1M tokens
$60.00/ 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.

o1

OpenAI

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.