# Evaluate Model: OpenAI Codex CLI 0.115.0: GPT-5.3-Codex Integration and Native Windows Support
## What This Is
The latest OpenAI Codex command-line tool introduces the new GPT-5.3-Codex model, delivering 25% faster performance for coding tasks. The update adds native support for Windows, advanced image analysis capabilities, and the ability to run multiple AI agents simultaneously on the same project.
Source: https://community.openai.com/t/codex-for-open-source-2026/1376418
## Before You Start
Scan my workspace and analyze:
- The project language, framework, and current AI integrations
- Existing AI provider config (check .env, .env.local, config files for API keys — OpenRouter, OpenAI, Anthropic, Google AI, etc.)
- Which AI models I currently use and for what purposes
Then ask me before proceeding:
1. Am I interested in evaluating this model for my project, or just want a summary of what it offers?
2. If I want to try it — which part of my current AI stack should it replace or complement?
## Source Access Note
The source URL (https://community.openai.com/t/codex-for-open-source-2026/1376418) may not be directly accessible from the terminal. Use the Reference Implementation and Additional Context sections below instead. If you need more details, ask me to paste relevant content from the source.
## What to Implement
This is a **New AI Model** — a model release, update, or capability announcement.
- Analyze the best use cases for this model within my project and current AI stack
- Compare its strengths, pricing, and context window against whatever I currently use
- Give me a clear, convincing argument for why this model would (or would not) be a good fit for my project
- If I want to try it: update my API configuration (provider, model ID, any new parameters) to point to this model
- If it requires a new API key or provider signup, tell me exactly what to do
## Additional Context
- Check the user's current OpenAI Codex CLI version by running `codex --version`. If it is older than 0.115.0, initiate the upgrade process using the appropriate package manager or by fetching the latest binary.
- Scan the user's project for visual assets (e.g., PNG, JPG files in UI mockups). Propose a new workflow that uses the `view_image` command to analyze these assets and generate corresponding code or documentation.
- Analyze the user's project structure to identify tasks that can be parallelized. Formulate a plan to configure isolated git worktrees and launch multiple Codex agents to work on separate branches simultaneously, leveraging the new multi-agent capabilities.
## Guidelines
- Adapt everything to my existing project — do not assume a specific stack or directory layout
- Use whichever AI provider I already have configured; if I need a new one, tell me what to sign up for and I'll give you the key
- Check my .env files for existing API keys (OpenRouter, OpenAI, Anthropic, Google AI) before asking me to add one
- Review any fetched code for safety before installing or executing it
- After setup, run a quick verification and show me a summary of exactly what was installed, where, and how to use it