Large Language Models are no longer simply autocomplete widgets in our IDEs. In 2026, developers rely on frontier models to conduct full-system legacy codebase migrations, architectural refactors, and rigorous unit test compilation. But which model produces code that compiles successfully on the first try?
The search for the "best programming LLM" is often clouded by marketing. Models boast high scores on synthetic tests like HumanEval, but these tests have leaked into training sets. To bypass this bias, the Dera editorial team designed a randomized complex refactoring checklist reflecting real-world enterprise engineering bottlenecks.
The Refactoring Benchmark
We challenged OpenAI o3-mini, Claude 3.5 Sonnet, and Gemini 2.5 Pro to refactor a legacy Node.js Express server to a modern TypeScript ES Module architecture. The prompt required the models to:
- Enforce strict TypeScript types on all middleware states.
- Replace all commonjs require statements with fully typed ESM imports.
- Compile without warnings under --noImplicitAny and --strictNullChecks flags.
- Resolve dynamic routing files asynchronously with dynamic imports.
| Evaluation Parameter | Claude 3.5 Sonnet | OpenAI o3-mini | Gemini 2.5 Pro |
|---|---|---|---|
| First-run Compilation Rate | 94% (Clean compilation, zero implicit any) | 89% (Missing exact type signature on express requests) | 81% (Correct types, but occasional typo in import suffixes) |
| Architectural Cleanliness | High. Modularized handlers perfectly. | Extremely High. Built precise, robust typings. | Moderate. Kept routes in a single large file. |
| Handling Edge Cases | Catches missing async catch blocks cleanly. | Deeply analyzes race conditions in routes. | Missed occasional error-capturing middlewares. |
| Token Economy & Overhead | Highly detailed commentary. | Direct, code-first with minimal conversational fluff. | Long explanations with detailed code blocks. |
Why Claude Maintains its Developer Lead
Anthropic’s Claude 3.5 Sonnet continues to excel at structured, modular TypeScript. While OpenAI’s o3-mini possesses rapid execution speeds and outstanding algorithmic processing power, Claude’s grasp of system design is superior. It consistently structures file modules cleanly, avoids putting everything in a single index.ts, and creates intuitive descriptive interfaces.
Claude 3.5 Sonnet acts like a communicative senior software architect. It doesn’t just solve the syntax; it structures the files exactly where they belong in real, scalable systems.
Gemini’s Massive Context Advantage
Where Gemini 2.5 Pro remains unmatched is sheer repository comprehension. We ingested our entire 5,000-line front-end codebase into Gemini’s context window. While other models started showing context dilution or forgetting file properties, Gemini successfully refactored dependencies across multiple sibling directories and corrected export discrepancies in seconds.
For individual, high-density modules, use Claude. For large, repository-wide architectural migrations, Gemini’s multi-million token window is a game-changer.