Claude Opus 4.6 Coding Test Results

Claude Opus 4.6 launched in March 2026 as Anthropic’s most capable model for coding tasks. We put it through 50 real-world coding tests and compared it head-to-head with GPT-5 (via ChatGPT Plus) to see whether the claims hold up.

The short answer: Opus 4.6 is the best coding model available to consumers right now, with caveats. Here are the full results.

Test Methodology

We designed 50 coding tasks across five categories, each with 10 tasks:

1. Simple generation — Write a function, component, or script from a clear specification
2. Complex refactoring — Restructure existing code, change patterns, migrate between frameworks
3. Debugging — Find and fix bugs in provided code with intentional errors
4. Code review — Analyze code for issues, suggest improvements, identify security concerns
5. Multi-file architecture — Design or modify systems spanning multiple files and modules

Languages tested: Python (20 tasks), TypeScript (20 tasks), Rust (10 tasks)

Scoring criteria: Each task was scored on four dimensions:

• Correctness — Does the code work? (0-25 points)
• Quality — Is the code clean, idiomatic, and maintainable? (0-25 points)
• Completeness — Does it handle edge cases and error conditions? (0-25 points)
• Speed — How quickly did the model produce the response? (0-25 points)

Maximum score per task: 100 points. All tests were run three times with the same prompts, and we report the average score.

Models tested:

• Claude Opus 4.6 via Claude Pro ($20/month)
• GPT-5 via ChatGPT Plus ($20/month)
• GPT-5.4 via ChatGPT Plus ($20/month)

Both services were tested at the same price point for fairness.

Overall Results

Opus 4.6 won three of five categories decisively and was competitive in the other two. GPT-5.4 (the newer ChatGPT model) narrowed the gap compared to base GPT-5 but still trailed Opus on complex tasks.

Category Breakdown

Simple Generation: GPT-5.4 Leads Narrowly

For straightforward tasks — write a React component, implement a sorting algorithm, create an API endpoint — all three models performed well. GPT-5.4 edged ahead with slightly faster responses and clean output formatting.

What we observed:

• GPT-5.4 produced working code faster on average (8 seconds vs 12 seconds for Opus)
• Opus code was marginally more thorough with type annotations and error handling
• GPT-5 base was slightly less consistent on TypeScript typing
• All three achieved 90%+ correctness rates on simple tasks

Verdict: For simple code generation, speed matters more than marginal quality differences. GPT-5.4 wins this category.

Complex Refactoring: Opus 4.6 Dominates

This is where Opus 4.6 separated itself. Refactoring tasks required understanding existing code, preserving behavior while changing structure, and handling interdependencies. Tasks included migrating a class-based React app to hooks, converting synchronous Python to async, and restructuring a monolithic Rust module into a workspace.

What we observed:

• Opus maintained context across large code blocks more reliably
• Opus identified side effects and dependencies that GPT-5 missed in 4 of 10 tasks
• GPT-5 occasionally broke existing functionality during refactoring (3 of 10 tasks had regressions)
• GPT-5.4 was better than GPT-5 but still introduced regressions in 2 of 10 tasks
• Opus preserved all existing tests in 9 of 10 tasks

Verdict: Opus 4.6 is significantly better at complex refactoring. The gap is large enough to influence subscription choice for developers doing regular refactoring work.

Debugging: Opus 4.6 Wins

We provided code with intentional bugs — off-by-one errors, race conditions, null reference issues, incorrect type coercions, and logic errors. Models needed to identify the bug, explain it, and provide a fix.

What we observed:

• Opus correctly identified the root cause in 9 of 10 tasks (GPT-5: 7, GPT-5.4: 8)
• Opus explanations were more detailed and referenced specific line numbers consistently
• GPT-5 occasionally fixed the symptom without identifying the root cause
• All three models handled simple bugs (off-by-one, null checks) equally well
• The difference emerged on subtle bugs: race conditions, closure scoping issues, type coercion edge cases

Verdict: Opus 4.6 is the better debugging partner, especially for subtle bugs that require deep code understanding.

Code Review: Opus 4.6 Wins Clearly

We asked each model to review code submissions for quality, security issues, performance concerns, and maintainability. This tested analytical capability rather than generation.

What we observed:

• Opus identified an average of 6.2 issues per review vs 4.8 for GPT-5 and 5.4 for GPT-5.4
• Opus caught 3 security concerns that GPT-5 missed entirely (SQL injection in a parameterized query variant, CORS misconfiguration, timing attack vulnerability)
• Opus reviews were structured more consistently with severity ratings
• GPT-5.4 reviews were good but occasionally missed performance issues that Opus caught

Verdict: Opus 4.6 is the strongest code review model. The security issue detection alone makes it valuable for teams reviewing code changes.

Multi-File Architecture: Opus 4.6 Wins

These tasks involved designing or modifying systems that span multiple files — setting up project structure, defining module boundaries, creating interfaces between components, and managing dependencies.

What we observed:

• Opus produced coherent multi-file outputs with correct import paths in 9 of 10 tasks
• GPT-5 had import path errors in 4 of 10 tasks (file references that did not match the generated structure)
• Opus consistently generated all necessary files, including configuration files (tsconfig, Cargo.toml, etc.)
• GPT-5.4 improved over GPT-5 but still missed configuration files in 2 of 10 tasks

Verdict: Opus 4.6 handles multi-file context significantly better. For developers working on architecture-level tasks, this is a meaningful advantage.

Speed Comparison

Across all 50 tasks, average response times:

Opus 4.6 is consistently slower — roughly 35-40% more time per response on average. For interactive coding sessions where you are waiting on each response, this is noticeable. For code review and architecture tasks where you review the output carefully anyway, the extra seconds are irrelevant.

Language-Specific Results

Python: Opus and GPT-5.4 tied at 84 average. Both produce idiomatic Python. Opus had better type hint usage; GPT-5.4 had slightly cleaner formatting.

TypeScript: Opus scored 87 vs GPT-5.4’s 80. The gap was largest here. Opus handled complex TypeScript generics and utility types more accurately and produced fewer type errors.

Rust: Opus scored 86 vs GPT-5.4’s 79. Opus better understood Rust ownership semantics and lifetime annotations. GPT-5 (base) struggled with lifetimes in 3 of 10 Rust tasks.

Who Benefits from Opus 4.6

Switch to Claude for coding if you:

• Do regular refactoring work across codebases
• Need reliable code review with security focus
• Work with TypeScript or Rust (where Opus’s advantage is largest)
• Handle multi-file architecture tasks
• Value correctness over speed

Stay with ChatGPT for coding if you:

• Primarily write new code (simple generation)
• Need fast response times for interactive pair programming
• Use image generation alongside coding (diagrams, UI mockups)
• Rely on ChatGPT plugins for your development workflow
• Work mostly in Python (where the models are closest)

Consider using both:

Some developers use Claude for complex tasks (refactoring, review, architecture) and ChatGPT for quick tasks (generate a function, explain an error, write a regex). This costs $37/month if you use Claude Pro annual ($17) and ChatGPT Plus ($20), but for professional developers the combined capability may justify it.

Subscription Implications

Opus 4.6 is available on Claude Pro at $20/month (or $17/month with annual billing). You get Opus 4.6 with usage limits — roughly enough for 50-80 substantial coding queries per day depending on context length.

Claude Max at $100/month removes those limits. Whether Max is worth 5x the price depends on volume: if you regularly exceed Pro’s limits, Max pays for itself in removed friction. For most developers, Pro is sufficient.

On the ChatGPT side, GPT-5 is available on Plus at $20/month. GPT-5.4 is also on Plus but with lower priority access compared to Pro ($200/month). For coding specifically, ChatGPT Plus gives you adequate GPT-5.4 access.

For a complete comparison of Claude and ChatGPT across all use cases (not just coding), see our Claude vs. ChatGPT head-to-head comparison. And for the broader coding landscape across all providers, our best AI for coding guide ranks every option.

Test Data Availability

We will publish the full test suite (all 50 tasks, prompts, and scored outputs) on our GitHub repository by mid-April. This allows independent verification and reproduction of our results.

Test methodology will remain consistent for future model comparisons, creating a longitudinal dataset across model generations. Our next planned test compares Gemini 2.5 Pro against these baselines.