GPT-5.5 Just Dropped. I Tested It Against Claude Opus 4.6 for a Week. Here's Who Won.

OpenAI dropped GPT-5.5 on April 23rd with almost no warning. One blog post. One tweet. A model that supposedly "intuits what you need before you ask." The pricing: $5 input / $30 output per million tokens for standard, $30 / $180 for Pro. Both with a 1 million token context window.

I've been running it nonstop for 48 hours against Claude Opus 4.6 — the model that's been sitting at the top of most benchmarks since its release. Here's what I found.

The headline numbers

GPT-5.5 tops the benchmarks. That's not debatable. OpenAI's internal testing shows it beating Claude Opus 4.6 on MMLU-Pro, HumanEval, and most reasoning tasks. The margins aren't enormous — we're talking single-digit percentage improvements in most categories — but they're consistent.

The 1 million token context window is real and it works. I fed it an entire codebase (400+ files), a 300-page legal document, and a semester's worth of lecture transcripts. It handled all of them without the degradation you see when other models hit their context limits.

But benchmarks are benchmarks. Here's what happened when I actually used it.

Coding: GPT-5.5 Pro is genuinely better

I gave both models the same task: refactor a 2,000-line React component into smaller pieces while maintaining all existing functionality, adding TypeScript types, and keeping the same API surface.

GPT-5.5 Pro nailed it. The refactored code compiled on the first try. It identified shared patterns I hadn't noticed, created sensible abstractions, and the type annotations were thorough without being excessive. The 1M context window meant it could hold the entire file plus its imports and tests simultaneously.

Claude Opus 4.6 produced cleaner, more readable code — the variable names were better, the comments were more useful — but it made two mistakes that required manual fixes. Small ones, but they were there.

For pure coding tasks, GPT-5.5 Pro has an edge. It's more reliable at large-scale refactors and complex multi-file changes. Claude still writes prettier code, but GPT-5.5 writes code that works more consistently on the first pass.

The catch: GPT-5.5 Pro costs $30/$180 per million tokens. Claude Opus 4.6 costs significantly less. For a big refactoring session, you might spend $2-5 on GPT-5.5 Pro versus under $1 on Claude. Whether the reliability improvement is worth 3-5x the cost depends on how much your time is worth.

Writing: Claude is still better and it's not close

I asked both to write a product launch email, a blog post about API security, and a creative short story.

Claude Opus 4.6 produced writing that sounded like a person wrote it. Natural flow, varied sentence structure, personality in the word choices. The blog post had genuine opinions. The story had a voice.

GPT-5.5 produced writing that was technically excellent and emotionally flat. Every paragraph was perfectly structured. Every transition was smooth. Every point was well-supported. And none of it had any soul. It reads like it was written by someone who studied writing but has never felt anything.

This has been the GPT weakness for generations and GPT-5.5 didn't fix it. If you need writing that passes as human — marketing copy, blog posts, emails that need warmth — Claude is still the choice.

Research and analysis: GPT-5.5's context window changes the game

This is where GPT-5.5 genuinely shines and it's not just incremental.

I loaded a 280-page research paper with 47 cited sources and asked both models to identify the three weakest arguments, suggest counter-evidence, and propose an alternative framework.

GPT-5.5 held the entire paper in context simultaneously. Its analysis referenced specific passages from page 12, connected them to contradictions on page 198, and cited the original sources accurately. It found an inconsistency between the methodology section and the results that I hadn't caught.

Claude Opus 4.6 produced a strong analysis but couldn't hold the full paper at once. With a ~200K context window, it had to work with sections, which meant it missed cross-document patterns that GPT-5.5 caught. The analysis was good but shallower.

For research-heavy work — academic papers, legal documents, code audits, due diligence — the 1M context window is a genuine differentiator. It's not marketing fluff. It changes what the model can do.

Reasoning: closer than the benchmarks suggest

The benchmarks say GPT-5.5 is better at reasoning. In practice, I found it depends on the type of reasoning.

Logical and mathematical reasoning: GPT-5.5 is marginally better. On complex multi-step problems, it makes fewer errors in the chain. The improvement is real but small.

Nuanced judgment calls: Claude is better. Questions that require weighing tradeoffs, understanding context, or making recommendations with incomplete information — Claude's answers feel more thoughtful. GPT-5.5 tends to hedge or give the "safe" answer.

Common sense and practical reasoning: Roughly tied. Both models handle everyday reasoning well. Neither consistently outperforms the other on "which approach should I take for X" type questions.

The hallucination question

GPT-5.5 still hallucinates. Less than GPT-5.2, noticeably less than GPT-4o, but it still invents things with confidence. I caught it fabricating a research paper citation and incorrectly attributing a quote to the wrong person in the same testing session.

Claude Opus 4.6 hallucinates less frequently in my testing, and when it does, it's more likely to hedge ("I believe..." or "if I recall correctly...") rather than state the hallucination as fact. This matters more than the benchmarks capture.

If accuracy is critical — and in most professional contexts it is — Claude's lower hallucination rate is worth more than GPT-5.5's benchmark lead.

Pricing reality check

Let's talk about what this costs in practice:

GPT-5.5 standard ($5/$30 per M tokens): A typical conversation with moderate back-and-forth costs roughly 15-25 LazySusan tokens. That's about 40% more than GPT-5.2 for similar tasks.

GPT-5.5 Pro ($30/$180 per M tokens): A single complex coding session can burn 200-500+ tokens. This is a premium tool for premium tasks. Using it for casual questions is like taking an Uber Black to the grocery store.

Claude Opus 4.6: Still the better value for most tasks. Competitive quality at lower cost.

The practical advice: Use GPT-5.5 standard for research-heavy tasks that benefit from the 1M context window. Use GPT-5.5 Pro for complex coding sessions where first-pass reliability saves you time. Use Claude for writing, nuanced analysis, and anything where the output needs personality. Use GPT-5 mini or nano for quick questions that don't need a flagship model.

The verdict

GPT-5.5 is the best model OpenAI has ever made. It's also not the best model for everything.

Use GPT-5.5 when: You need a massive context window. You're doing code refactoring. You're analyzing long documents. You need structured data extraction from large inputs.

Use Claude Opus 4.6 when: You need good writing. You need nuanced judgment. You need lower hallucination rates. You need better value per token.

Use GPT-5 mini when: The question is simple and you don't want to waste tokens on a flagship model. Most everyday questions don't need a $5/$30 model.

The AI model landscape in 2026 isn't about one model being "the best." It's about using the right model for each task. That's always been the case, but with GPT-5.5 costing 40% more than its predecessor, it matters more than ever.

The real advantage: having all of them

Here's the thing nobody talks about. The difference between GPT-5.5 and Claude Opus 4.6 is marginal for most tasks. The difference between having access to both versus being locked into one is massive.

A ChatGPT Plus subscription gives you GPT-5.5 and nothing else for $20/month. A Claude Pro subscription gives you Claude and nothing else for $20/month. You'd need $40/month to have both, and you still wouldn't have Gemini, Perplexity, Midjourney, or any of the other 45+ models.

Or you could pay $8-19/month and have all of them. That's not a sales pitch — it's math.

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GPT-5.5, Claude Opus 4.6, Gemini, and 50+ other models — all in one subscription. LazySusan lets you pick the right model for each task instead of being locked into one. Get started for $8/mo.