Tested Claude 4 Opus vs Grok 4 on 15 Rust coding tasks - actual numbers inside
Ran both models through identical coding challenges on a 30k-line Rust codebase. Here's what the data shows: **Bug Detection:** Cursor 4 caught every race condition and deadlock I threw at it. Opus missed several, including a tokio::RwLock deadlock and a thread drop that prevented panic hooks from executing. **Speed:** Cursor averaged 9-15 seconds, Opus 13-24 seconds per request. **Cost:** $4.50 vs $13 per task. But Cursor's pricing doubles after 128k tokens. **Rate Limits:** Cursor's limits are brutal. Constantly hit walls during testing. Opus has no such issues. **Tool Calling:** Both at 99% accuracy with JSON schemas. XML dropped to 83% (Opus) and 78% (Cursor). **Rule Following:** Opus followed my custom coding rules perfectly. Cursor ignored them in 2/15 tasks. **Single-prompt success:** 9/15 for Cursor, 8/15 for Opus. **Bottom line:** Cursor is faster, cheaper, and better at finding hard bugs. But the rate limits are infuriating and it occasionally ignores instructions. Opus is slower and pricier but predictable and reliable. For bug hunting on a budget: Cursor. For production workflows where reliability matters: Opus. Full breakdown [here](https://forgecode.dev/blog/cursor-4-opus-vs-cursor-4-comparison-full/) Anyone else tested these on real codebases? Curious about experiences with other languages.
Agent Library is a centralized collection of reusable AI agent skills, workflows, prompts, and specialized knowledge modules. Built for Claude Code, Codex, Cursor, and other AI coding agents with an efficient on-demand loading architecture.
An open-source collection of production-ready AI skills, prompts, templates, and workflows for Claude, ChatGPT, Gemini, Cursor, and other AI tools.
A collection of Skills (system prompts) for autonomous AI Agents and LLMs (Google Antigravity, Claude Code, GitHub Copilot, Codex, Cursor, AutoGPT, ChatGPT, Gemini).
许惟的 AI 工具合集 · A growing collection of practical AI tools & skills. First up: diagram-generator (one sentence → clean diagrams).
A curated collection of high-quality AI prompts for ChatGPT, Claude, Gemini, Cursor, and other AI assistants
A curated collection of ready-to-run automation prompts for real-world workflows.
Workflows from the Neura Market marketplace related to this Cursor resource