LLM ComparisonGPT-5 CodexGemini 3 Pro

GPT-5 Codex vs Gemini 3 Pro

Compare GPT-5 Codex and Gemini 3 Pro. Build AI products powered by either model on Appaca.

Model Comparison

FeatureGPT-5 CodexGemini 3 Pro
ProviderOpenAIGoogle
Model Typetexttext
Context Window400,000 tokens1,000,000 tokens
Input Cost
$1.25/ 1M tokens
$4.00/ 1M tokens
Output Cost
$10.00/ 1M tokens
$18.00/ 1M tokens

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Strengths & Best Use Cases

GPT-5 Codex

OpenAI

1. Purpose-Built for Agentic Coding

  • Optimized specifically for scenarios where the model must act as an autonomous or semi-autonomous coding agent.
  • Tailored for Codex workflows such as planning, editing, debugging, and multi-step tool-driven code tasks.

2. Advanced Coding Reasoning

  • Extends GPT-5's higher reasoning mode to better handle complex software logic and multi-file dependencies.
  • Produces more accurate, structured, and maintainable code across modern programming languages.

3. Strong Tool Use in Developer-Like Environments

  • Designed for Codex's agent environment, enabling the model to:
    • Read and modify files
    • Follow function signatures and API contracts
    • Navigate codebases with awareness of context and structure

4. Large Context Window for Full-Project Understanding

  • 400,000-token context allows ingestion of:
    • Entire repositories
    • Multiple files at once
    • Architectural descriptions
  • Enables long-range reasoning across codebases rather than isolated snippets.

5. Multimodal Capability for Development Tasks

  • Accepts text and image as input (great for screenshots of error logs, UI mocks, whiteboards).
  • Outputs text only, focusing its output precision on code, reasoning, and documentation.

6. Continuous Snapshot Updates

  • The underlying model version is regularly upgraded behind the scenes.
  • Ensures developers always use the best coding-enhanced GPT-5 variant without changing model names.

7. Reliable Instruction Following

  • Very strong adherence to constraints like:
    • File/folder structure requirements
    • Framework conventions
    • Naming patterns
    • Linting rules
  • Makes it suitable for production coding agents.

8. Broad API Integration

  • Available only in the Responses API, giving you:
    • Streaming
    • Structured outputs
    • Function calling
  • Allows creation of interactive coding tools and agent workflows with tight model control.

Gemini 3 Pro

Google

1. State-of-the-art reasoning

  • Top performance across academic reasoning, scientific knowledge, math, and complex problem-solving.
  • Excels at long-horizon, multi-step workflows and deep logical interpretation.

2. World-leading multimodal capabilities

  • Natively understands text, images, videos, audio, and code.
  • Ranked highest on benchmarks like MMMU-Pro, Video-MMMU, ScreenSpot-Pro.

3. Exceptional coding + agentic workflows

  • Strong in competitive coding and real-world agentic tasks (SWE-Bench Verified, Terminal-Bench, LiveCodeBench).
  • Improved tool calling, planning, and execution for autonomous or semi-autonomous agents.

4. Powerful for long-context tasks

  • Effective at 128K-1M context windows with high retrieval accuracy.
  • Ideal for document-heavy workflows, research, analysis, multi-file coding, and multi-document reasoning.

5. Strong information synthesis and interpretation

  • Outperforms peers in chart reasoning, OCR, structured extraction, and screen understanding.
  • Excellent at combining multimodal inputs into coherent, concise answers.

6. High reliability for enterprise tasks

  • Benchmarks show superior factuality, grounding, and parametric knowledge.
  • Strong multilingual accuracy and global commonsense performance.

7. Optimized for production agents

  • Designed for complex multi-step planning, simultaneous task execution, and improved consistency.
  • Works across coding, research, creative workflows, UI generation, and data-heavy applications.

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