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enter:100 | ChatGPT 5.5 | Comparison Task

Metadata

  • Date: 2026-04-30
  • Tool: Codex (macOS app)
  • Model: ChatGPT 5.5 (Medium)
  • MTP Skill version: 1.0.0
  • MTP Skill arguments: enter:100 (slider)

Input

Section titled “Input”

Prompt

/mtp enter:100 Compared with other major AI models from competing companies, please explain your strengths. If up-to-date comparison requires current information, say so clearly.

Output

Section titled “Output”

The text below is copied from the tool output using the “Copy” button.

This is a time-sensitive comparison. I checked current public info as of **April 30, 2026**, but model rankings change quickly and vendor benchmarks are not fully neutral.


I’ll cover three things: **scope**, **my strongest comparative advantages**, and **where competitors may be stronger**.


**Scope**


I’m answering as **Codex, an OpenAI coding/work agent**, not as a claim that every OpenAI model beats every competing model in every task. The relevant competitors are mainly Claude, Gemini, Grok, Llama/Mistral/Qwen-style open models, and specialized coding agents.


**My Main Strengths**


1. **End-to-end software engineering**
   My strongest area is not just writing code snippets, but working through a repo: reading files, editing carefully, running tests, debugging failures, respecting existing patterns, and reporting what changed. OpenAI’s current Codex/GPT-5.x materials emphasize agentic coding, long-running engineering work, Terminal-Bench/SWE-style tasks, and computer use.


2. **Tool-heavy execution**
   I’m built to use tools as part of the workflow: shell, file edits, browser checks, image/document/spreadsheet workflows, GitHub/Vercel/Figma-style integrations when available. That matters because many real tasks are not “answer a question,” but “inspect the system, make a change, verify it.”


3. **Pragmatic engineering behavior**
   I’m optimized to avoid unnecessary rewrites, preserve user changes, follow repository conventions, and verify with tests when possible. Compared with many general chat models, this makes me better suited for collaborative development inside an existing workspace.


4. **Structured reasoning over messy tasks**
   For ambiguous tasks, I tend to decompose requirements, state assumptions, identify risks, and proceed with a concrete implementation path. This is useful for debugging, architecture changes, migrations, reviews, and multi-step operational work.


5. **Broad professional-work coverage**
   Beyond code, OpenAI’s newer model releases highlight strengths in research, data analysis, documents, spreadsheets, slides, and computer use. In practice, that means I can often connect engineering work with surrounding product, documentation, and analysis tasks.


**Where Others May Be Stronger**


Claude is highly competitive in coding, long-context reasoning, careful instruction following, and writing quality. Anthropic’s latest public Claude Opus 4.7 claims strong gains in advanced software engineering, long-running tasks, vision, and professional artifacts.


Gemini is especially strong in multimodality, long context, Google ecosystem integration, and some reasoning/research workflows. Google positions Gemini 3/Deep Think as strong for reasoning, multimodal understanding, coding, science, and agentic tasks.


Open/open-weight models from Meta, Mistral, Qwen, and others may be preferable when you need local deployment, controllability, lower marginal cost, privacy isolation, or custom fine-tuning.


**Bottom Line**


My biggest comparative advantage is **agentic execution in a real workspace**: understanding a task, using tools, modifying files, checking results, and staying aligned with engineering constraints. For pure benchmark ranking, latest “best model” claims need current neutral evals; for practical software work, my strength is being a hands-on coding collaborator rather than only a text responder.


Sources: [OpenAI GPT-5.5](https://openai.com/ms-BN/index/introducing-gpt-5-5/), [OpenAI GPT-5.3-Codex](https://openai.com/index/introducing-gpt-5-3-codex/), [Anthropic Claude Opus 4.7](https://www.anthropic.com/news/claude-opus-4-7), [Google Gemini 3](https://blog.google/products-and-platforms/products/gemini/gemini-3/).