GPT-5 Pro vs o3

Compare GPT-5 Pro and o3. Find out which one is better for your use case.

Model Comparison

FeatureGPT-5 Proo3
ProviderOpenAIOpenAI
Model Typetexttext
Context Window400,000 tokens200,000 tokens
Input Cost$15.00 / 1M tokens$2.00 / 1M tokens
Output Cost$120.00 / 1M tokens$8.00 / 1M tokens

Strengths & Best Use Cases

GPT-5 Pro

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.

o3

1. Advanced reasoning capability

  • Designed for multi-step thinking across text, code, and visual inputs.
  • Excels at math, science, logic puzzles, and complex analytical workflows.

2. Strong performance across domains

  • Highly capable in technical writing, data analysis, and structured problem-solving.
  • Useful for research, engineering tasks, and intricate instruction-following.

3. Visual reasoning support

  • Accepts image inputs, enabling tasks such as diagram analysis, chart interpretation, and visual logic assessments.

4. High output capacity

  • Up to 100,000 output tokens, supporting long-form content, technical breakdowns, and multi-part solutions.

5. Excellent instruction following

  • Produces detailed, step-by-step responses for tasks requiring precision and clarity.
  • Ideal for educational explanations, system design reasoning, and code walkthroughs.

6. Large 200K context window

  • Handles long documents, multi-file reasoning, or extended conversations with minimal loss of context.

7. Broad API support

  • Works with Chat Completions, Responses, Realtime, Assistants, Batch, Embeddings, Image Generation, and more.
  • Supports streaming and function calling for advanced workflows.

8. Positioned as a legacy reasoning model

  • Remains extremely capable but formally succeeded by GPT-5, which offers stronger reasoning and performance.

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