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LLM ComparisonGPT-5 CodexGemini 2.5 Pro Experimental

GPT-5 Codex vs Gemini 2.5 Pro Experimental

Compare GPT-5 Codex and Gemini 2.5 Pro Experimental. Build AI products powered by either model on Appaca.

Model Comparison

FeatureGPT-5 CodexGemini 2.5 Pro Experimental
ProviderOpenAIGoogle
Model Typetexttext
Context Window400,000 tokens1,048,576 tokens
Input Cost
$1.25/ 1M tokens
$1.50/ 1M tokens
Output Cost
$10.00/ 1M tokens
$6.00/ 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 2.5 Pro Experimental

Google

1. State-of-the-art reasoning performance

  • #1 on LMArena human preference leaderboard.
  • Excels at advanced reasoning benchmarks like GPQA and AIME 2025.
  • Achieves 18.8% on Humanity's Last Exam (no tools), representing frontier human-level reasoning.

2. New “thinking model” architecture

  • Built with explicit reasoning steps internally before responding.
  • Handles complex, multi-stage logic with higher accuracy and fewer hallucinations.

3. Elite science and mathematics capabilities

  • Leads in math and science tasks across industry benchmarks.
  • High performance without costly inference tricks like majority voting.

4. Exceptional coding abilities

  • Major leap over Gemini 2.0 in coding performance.
  • 63.8% on SWE-Bench Verified with custom agent setup.
  • Strong at code transformation, debugging, and building agentic apps.
  • Capable of generating full applications (e.g., a playable video game) from a single-line prompt.

5. Massive multimodal context

  • Ships with a 1,000,000 token window (2M coming soon).
  • Handles entire documents, datasets, video sequences, audio files, and large codebases.
  • Maintains strong performance even at extreme context lengths.

6. Native multimodality across all inputs

  • Understands and reasons over text, images, audio, video, and code.
  • Designed for real-world, multi-source problem-solving and agent workflows.

7. Consistent high-quality outputs

  • Improved post-training results in more accurate, coherent, and stylistically strong responses.
  • Higher reliability across complex workloads.

8. Early availability for developers

  • Available today in Google AI Studio for experimentation.
  • Coming soon to Vertex AI with higher rate limits and production-ready access.