GPT-5.5 Codex vs Claude Opus 4.7: Real-world coding agent benchmarks
A Reddit user tested GPT-5.5 Codex (via Cursor) against Claude Opus 4.7 (Claude Code) on two production-grade tasks. Both used the same prompts, MCPs (GitHub + Slack), and machine. Results highlight tradeoffs in cost, architecture, and reliability.
Test 1: PR triage bot
- GitHub MCP, scoring formula, Slack alerts, retries, strict TypeScript (no
any). - Claude Code: Verified MCP reachable before writing code. Built 36 files in 12 minutes. Wrote its own WebSocket smoke test (3ms broadcast). Zero errors on first run. Total cost: ~$2.50.
- Codex: Failed — GitHub MCP unreachable due to Cursor environment issue (not model error). Could not complete task.
Test 2: Real-time code review UI
- React, WebSockets, optimistic rollback, virtualized diff, WS reconnect.
- Claude Code: Same clean delivery, 36 files, no errors.
- Codex: Shipped in 28 files (more compact architecture). Required one manual patch for an infinite React loop. Total cost: ~$2.04 (18% cheaper than Claude).
Takeaways: For complex, architecture-heavy work, Opus 4.7 still leads — better tool handling, zero-rewrite output, and thorough MCP validation. Codex is leaner and cheaper, suitable for tight, self-contained tasks where fast shipping matters and you can tolerate a minor patch pass. The user isn't switching yet but now watches the pricing gap.
📖 Read the full source: r/ClaudeAI
👀 See Also
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context-os: Open-source tool reduces Claude Code token consumption by 27-42%
context-os is a local context optimizer that hooks into Claude Code automatically, compressing tool output before Claude sees it and reducing token consumption by 27-42% depending on content type.
ReasonDB: Open-Source Document Database Using LLM-Guided Tree Navigation Instead of Vector Search
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