GPT-5.2 vs o1-pro

Compare GPT-5.2 and o1-pro. Find out which model is better for your specific use case and requirements.

Model Comparison

FeatureGPT-5.2o1-pro
ProviderOpenAIOpenAI
Model Typetexttext
Context Window400,000 tokens200,000 tokens
Input Cost
$1.75/ 1M tokens
$150.00/ 1M tokens
Output Cost
$14.00/ 1M tokens
$600.00/ 1M tokens

Strengths & Best Use Cases

GPT-5.2

OpenAI

1. Advanced Reasoning for Diverse Domains

  • Built to tackle coding and agentic workflows across multiple industries, with configurable reasoning support.

2. Multi-Modal & Long-Form Capabilities

  • Handles both text and image inputs, producing text output:contentReference[oaicite:1]{index=1}.
  • Allows up to 128 k output tokens for lengthy responses:contentReference[oaicite:2]{index=2}.

3. Large Context & Updated Knowledge

  • 400 k token context window accommodates extensive codebases or documents:contentReference[oaicite:3]{index=3}.
  • Knowledge cut-off of Aug 31 2025 keeps it current with recent developments:contentReference[oaicite:4]{index=4}.

o1-pro

OpenAI

1. Maximum-compute o-series model

  • Uses significantly more compute per query compared to o1.
  • Produces deeper, more reliable reasoning chains.
  • Best suited for high-stakes tasks that need correctness over speed.

2. Trained with reinforcement learning for deliberate thinking

  • Explicit "think-before-answer" architecture.
  • Excels at complex reasoning requiring multi-step analysis.

3. Very strong at math, science, coding, and technical proofs

  • Handles long derivations, algorithm design, and difficult logic problems.
  • Produces structured and explainable reasoning trails.

4. Great for multi-turn reasoning workflows

  • Responses API optimized: can think over multiple internal turns before responding.
  • Ideal for agentic reasoning pipelines.

5. Large context window

  • 200,000-token context for large documents, multi-file review, and long reasoning traces.

6. Multimodal input (text + image)

  • Can analyze images for mathematical diagrams, charts, handwritten content, UI layouts, etc.
  • Output is text only.

7. Consistency, reliability, and depth

  • Designed for situations where accuracy matters more than latency or cost.
  • Strong error-checking and self-correction abilities.

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