abyss: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: abyss:100 (slider)

Input

Prompt

/mtp abyss: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

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

Up-to-date comparison **does require current information**. Frontier-model rankings change quickly, and vendor benchmark claims are not the same as independent evals. As of checking current official/product sources, Anthropic is promoting Claude Opus 4.7 for coding, agents, vision, and multi-step work; Google is promoting Gemini 3.1 Pro / Gemini 3 Deep Think for complex reasoning, research, and engineering; xAI’s latest public emphasis is Grok voice/API capability; OpenAI’s Codex line emphasizes agentic coding and real computer work.

My main strengths in this Codex setting are:

1. **End-to-end software execution, not just advice.**
   I can inspect a repo, edit files, run tests, read failures, patch again, and report exactly what changed. On the surface, this is “coding help”; beneath it, the real strength is that my answers can be forced through the discipline of a working environment.

2. **Agentic software work.**
   I am strongest where the task has many small decisions: debugging, refactors, migrations, review comments, build failures, test gaps, documentation tied to code, and “make this actually work” workflows.

3. **Tool-grounded reasoning.**
   When facts are unstable, I can browse; when code is uncertain, I can run it; when files matter, I can inspect them. That reduces pure-memory failure. The advantage is not omniscience, but a bias toward checking reality.

4. **Pragmatic engineering judgment.**
   I tend to preserve existing patterns, avoid unrelated churn, protect user changes, and verify with tests where possible. This matters more than raw benchmark intelligence in real codebases.

5. **Interactive collaboration.**
   I can keep working while giving progress updates, adapt to corrections, and treat the workspace as shared state rather than a one-shot prompt/answer exchange.

Where competitors may be stronger depends on the task: Claude is often praised for long-form prose, careful conversational texture, and large-context work; Gemini has deep integration with Google’s multimodal and research stack; xAI/Grok emphasizes real-time product surfaces like X and voice. For a current leaderboard-style comparison, I would want fresh independent benchmarks, not only vendor claims.

Sources checked: [OpenAI GPT-5.3-Codex](https://openai.com/index/introducing-gpt-5-3-codex), [Anthropic newsroom](https://www.anthropic.com/news), [Google Gemini 3.1 Pro](https://blog.google/innovation-and-ai/models-and-research/gemini-models/gemini-3-1-pro/), [Google Gemini 3 Deep Think](https://blog.google/innovation-and-ai/models-and-research/gemini-models/gemini-3-deep-think/), [xAI latest news](https://x.ai/).