GPT-5 Pro vs Gemini 1.5 Pro

Compare GPT-5 Pro and Gemini 1.5 Pro. Find out which one is better for your use case.

Model Comparison

FeatureGPT-5 ProGemini 1.5 Pro
ProviderOpenAIGoogle
Model Typetexttext
Context Window400,000 tokens1,000,000 tokens
Input Cost$15.00 / 1M tokens$3.50 / 1M tokens
Output Cost$120.00 / 1M tokens$7.00 / 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.

Gemini 1.5 Pro

1. Breakthrough long-context window up to 1,000,000 tokens

  • Can process 1 hour of video, 11 hours of audio, 700k+ words, or 100k+ lines of code in a single prompt.
  • Supports advanced retrieval, reasoning, summarization, and cross-document tasks.
  • Achieves 99% retrieval accuracy on 1M-token Needle-In-A-Haystack tests.

2. Strong multimodal reasoning across video, audio, images, and text

  • Can analyze long videos (e.g., full silent films), track events, infer causality, and identify small details.
  • Handles large complex documents like manuals, transcripts, and books.

3. High-performance reasoning and problem solving

  • Comparable to Gemini 1.0 Ultra across many benchmarks.
  • Excels at code reasoning, multi-step explanations, and large-scale codebase analysis.

4. Advanced code understanding and generation

  • Performs problem-solving on codebases exceeding 100,000 lines.
  • Capable of cross-file reasoning, debugging guidance, API comprehension, and generating structured code improvements.

5. Efficient Mixture-of-Experts (MoE) architecture

  • Activates only relevant expert pathways per input.
  • Enables faster training, lower latency, and more efficient serving.
  • Dramatically improves scalability and inference speed.

6. Exceptional in-context learning capabilities

  • Learns new tasks directly from long prompts without fine-tuning.
  • Demonstrated by learning to translate a low-resource language (Kalamang) from a grammar manual.

7. High-fidelity multimodal understanding

  • Reads, analyzes, and reasons about long PDFs, code repositories, images, and videos together.
  • Enables new classes of applications: legal analysis, scientific review, codebase audits, long-form content generation, etc.

8. Safety and reliability first

  • Undergoes extensive ethics, safety testing, and red-teaming.
  • Improved representational safety and reduced hallucinations compared to previous generations.

9. Available for developers and enterprises

  • Accessible via AI Studio and Vertex AI.
  • Supports future pricing tiers for expanded context windows.
  • Designed for real enterprise-scale workloads.

10. Widely capable mid-size model

  • Positioned between Gemini Pro and Gemini Ultra generations.
  • Well-balanced: reasoning, multimodality, long-context, and speed.

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