Claude Opus 4.8 vs GPT-5.5: Which Is Better in August 2026?

The short version of Claude Opus 4.8 vs GPT-5.5: Opus 4.8 wins the hard stuff by a hair, and GPT-5.5 is the fast all-rounder that rarely feels like the weaker pick. When Artificial Analysis scored both on its Intelligence Index in June 2026, Opus 4.8 led at 61.4 to GPT-5.5's 60.2. That gap is 1.2 points. Read it again before you switch anything, because 1.2 points across a composite benchmark is not the chasm a leaderboard ranking makes it look like.

An August 2026 update sits on top of that: neither of these is its maker's newest model anymore. OpenAI shipped the GPT-5.6 family in July, Anthropic followed with Claude Opus 5 on July 24, and the top of the live leaderboard now belongs to the successors. Both models in this head-to-head are still available and still heavily used, so the useful question is narrower than "which model wins": which one wins for the thing you are about to do, and when it is worth stepping up a generation instead. Below is the per-category breakdown, the verdicts I actually stand behind after running both on real work, and the honest places each one stumbles.

The quick verdict

Claude Opus 4.8 is the model I reach for when the answer has to be right and I am willing to wait a beat for it: hard reasoning, multi-step science, code that has to survive contact with a real terminal. GPT-5.5 is the one I reach for when I want a strong, fast, broadly capable model that almost never feels like the weaker pick. Both released in spring 2026. Opus 4.8 landed May 28. GPT-5.5 arrived a little earlier, on April 23.

• Pick Opus 4.8 for: agentic coding, terminal-heavy tasks, scientific reasoning, and any answer where being wrong is expensive.

• Pick GPT-5.5 for: fast general work, writing, summarizing, and a model that is rarely the bottleneck on everyday tasks.

• Honest truth: for most prompts you would not reliably tell their answers apart in a blind test. The gap shows up on the hard stuff.

What changed since these two launched

This piece compares two spring 2026 flagships, and the summer moved fast, so here is the state of play as of August 2026. OpenAI's GPT-5.6 family reached general availability on July 9, 2026 in three builds: Luna, Terra, and Sol, in rising order of capability. On August 6, OpenAI made free ChatGPT messages unlimited on the Luna build, with ads rolling out and caps still in place on files, images, voice, and tools. Anthropic released Claude Opus 5 on July 24, 2026 at the same $5 / $25 per million token API price as Opus 4.8, and as of August 2026 Opus 5 holds the top spot on the Artificial Analysis Intelligence Index, with GPT-5.6 Sol as OpenAI's strongest entry close behind.

None of that makes this matchup moot. Opus 4.8 and GPT-5.5 are still live, supported models, and the per-task pattern below (Claude for the hardest reasoning and agentic work, GPT for fast general work) has been the stable shape of this rivalry for several generations. Prices are moving too: Anthropic is running Claude Sonnet 5 at an introductory API price of $2 / $10 per million tokens through August 31, 2026 (then $3 / $15), and OpenAI cut the price of GPT-5.6 Luna by 80 percent on July 30. We track the broader squeeze in our piece on the AI price war of 2026.

Claude Opus 4.8 vs GPT-5.5 on the benchmarks

The cleanest single number for a Claude vs GPT benchmark comparison is the Artificial Analysis Intelligence Index, a composite that blends reasoning, coding, math, and science evals into one score. When these two models were benchmarked on it in June 2026, Opus 4.8 sat at 61.4 and GPT-5.5 (at its highest reasoning setting, xhigh) sat at 60.2. For context, the previous Claude flagship, Opus 4.7, scored 57.3, so Opus 4.8 jumped 4.1 points over its own predecessor. That generational leap is bigger than the gap to GPT-5.5. One note before the table: Artificial Analysis has since rebased its index and added the newer flagships, so treat these as launch-window scores rather than today's live leaderboard numbers.

On price, the two are nearly even. Opus 4.8 standard API pricing is $5 per million input tokens and $25 per million output; GPT-5.5 is $5 in and $30 out. Anthropic also sells a faster "fast mode" for Opus at $10 / $50 per million, which it notes is three times cheaper than the fast mode on prior models. With stickers this close, the real per-answer cost difference comes from reasoning: how many thinking tokens each model spends before it answers, which you can influence with the effort setting covered below.

Reasoning and science

This is where Opus 4.8 earns its top spot. Artificial Analysis credits it with leading on GDPval-AA and with real gains in scientific reasoning, including CritPt physics and Humanity's Last Exam, over the prior generation. If you throw a genuinely hard multi-step problem at both, a proof sketch, a physics derivation, a research question that needs the model to hold a chain of logic without dropping a link, Opus 4.8 is the one that tends to keep its footing. It is also the model I trust more to say "I am not sure" instead of confidently inventing a tidy wrong answer.

Both of these are reasoning models, meaning they spend extra compute thinking before they answer. That is exactly why the gap between them widens on hard problems and shrinks to nothing on easy ones. On a quick factual lookup, the thinking budget barely matters. On a tricky derivation, it is the whole game.

Coding

Claude has a long reputation as the coder's model, and Opus 4.8 does not break the streak. Artificial Analysis reports it improved on Terminal-Bench Hard by 6.8 points over Opus 4.7, which is the kind of eval that maps to real agentic work: running commands, reading output, fixing what broke, trying again. That is the loop that matters when an AI is editing files in a live repo rather than handing you a snippet to paste somewhere. For that loop, Opus 4.8 is my default.

GPT-5.5 is not far behind, and on plenty of coding sessions it is the snappier experience. If you want a fast pair-programmer for everyday feature work, autocomplete-style help, or quick refactors, GPT-5.5 holds its own and often returns answers sooner. If you are debugging something gnarly across many files and you want the model to grind through it carefully, Opus 4.8 is worth the extra wait. I dug into this tradeoff more in our guide to the best AI app for coding.

Writing and everyday tasks

Here the benchmark gap stops mattering. For drafting, editing, summarizing, brainstorming, and the long tail of ordinary prompts, both are excellent and the difference comes down to taste. GPT-5.5 tends to feel a touch more eager and direct. Claude tends to feel more measured and careful with nuance. Neither is correct in the abstract. The one I prefer depends on the document, the tone, and frankly my mood that afternoon. This is the strongest argument for not marrying a single model.

Speed, cost, and the reasoning dial

Raw smarts is only half the decision. The other half is what the answer costs you in money and seconds. Opus 4.8 lists at $5 per million input tokens and $25 per million output on the standard tier, with the $10 / $50 fast mode as the low-latency option. GPT-5.5 lists at $5 in and $30 out. Those stickers are close enough that the practical takeaway is unchanged: the more deliberate model is usually the slower one per answer, and that tradeoff is the real reason to keep more than one on hand.

Both models also let you turn reasoning up or down, and that dial matters more than most people realize. GPT-5.5's headline 60.2 was measured at its xhigh setting; drop the effort and you trade some accuracy for a faster, cheaper response. The sane default on either model is a middle setting: reserve maximum effort for genuinely hard math, coding, and science, where the extra thinking earns its keep, and dial it back for routine prompts where it just burns tokens and time for no measurable gain. More thinking is not free, and past a point it can even talk a model out of a correct answer. Our guide to controlling AI reasoning effort covers the mechanics. The honest question ends up being which model is smarter at the effort level you are actually willing to pay for.

Where each model actually wins

Reviews that crown one model and bury the other are usually selling something. Here is the honest split, by task, with no thumb on the scale.

Notice how lopsided the wins look toward Opus 4.8, then notice what kind of tasks they are: the hardest ones. That is the whole story of a 1.2-point index gap. The leader pulls ahead at the top of the difficulty curve and ties everywhere else. If your week is mostly emails, summaries, and code that is not on fire, GPT-5.5 will serve you just fine and you will rarely feel the difference.

The benchmark caveat nobody mentions

A 1.2-point lead on a composite index is real, but it is also fragile. These scores move when a model gets an update, when an eval is refreshed, or when the index itself is rebuilt, and this summer delivered all three: new flagships shipped, Artificial Analysis rebased its index, and the launch-day 61.4 and 60.2 stopped being the live numbers. GPT-5.5's 60.2 was its xhigh result; dial the effort down and the number drops. Benchmarks are a snapshot, and treating a single index number as gospel is how people end up loyal to the wrong model for six months.

There is also a quiet limit on both: long-context reasoning. Both advertise a 1M token window, but a big window does not mean a model reasons well across all of it. Artificial Analysis built a long-context reasoning eval (AA-LCR) precisely because, as they put it, a large context window does not guarantee a model can reason effectively over long documents. Even frontier models score well below their headline benchmarks there, with top results clustering around 75 percent and the hardest tasks dropping under 50 percent. So if you are dumping a 300-page PDF into either model and expecting flawless synthesis, temper that expectation. Both will miss things in the middle.

You do not actually have to choose

Here is the part that changes the whole question. The premise of Claude Opus 4.8 vs GPT-5.5 assumes you pick one and commit. You do not have to. The smarter setup is to keep both within reach and route each task to whichever model is stronger for it.

That is exactly how I use them in MultiChats. One subscription puts both Opus 4.8 and GPT-5.5 in the same app, alongside Gemini, Grok, and 25+ models in total, and the successor generation is there too: Claude Opus 5 and the GPT-5.6 lineup are both available. I can start a thread on GPT-5.5, hit a hard subproblem, and switch models mid-conversation to Opus 4.8, or straight to Opus 5, without losing the thread. The context carries over. No new tab, no copy-paste, no second subscription.

If you want the wider field, our breakdown of ChatGPT vs Claude goes deeper on the two ecosystems, and the three-way ChatGPT vs Claude vs Gemini comparison adds Google's flagship to the mix. The pattern is consistent across all of them: no single model wins everything, so the people getting the most out of AI are the ones who stopped trying to crown one.

Frequently asked questions

Is Claude Opus 4.8 better than GPT-5.5?

At launch, yes, narrowly: Opus 4.8 scored 61.4 to GPT-5.5's 60.2 on the Artificial Analysis Intelligence Index as measured in June 2026, and that made it the top-ranked model of its moment. The 1.2-point gap mostly shows up on the hardest reasoning, coding, and science tasks; for routine work the two are close enough that most people would not notice a difference. As of August 2026 neither is the overall leader anymore: that spot belongs to Claude Opus 5.

Which is better for coding, Opus 4.8 or GPT-5.5?

For agentic and terminal-heavy coding, Opus 4.8, which improved on Terminal-Bench Hard by 6.8 points over the previous Claude flagship. For fast everyday coding, autocomplete-style help, and quick refactors, GPT-5.5 is strong and often quicker. If your work is debugging hard problems across many files, lean Opus. If it is rapid iteration, GPT-5.5 keeps up fine.

What is the smartest AI model in 2026?

As of August 2026, Claude Opus 5, released July 24, holds the number one spot on the Artificial Analysis Intelligence Index, with GPT-5.6 Sol as OpenAI's strongest entry close behind. Opus 4.8 held that same spot from late May until its successor arrived. "Smartest" depends on the task, though. The best AI model for your work is the one that wins the category you spend the most time in.

Can I use both Claude and GPT in one app?

Yes. MultiChats gives you Claude Opus 4.8, GPT-5.5, and 25+ models under one subscription, including Claude Opus 5 and the GPT-5.6 family, and you can switch between them mid-conversation while keeping the same thread and context. That removes the whole "which one do I commit to" problem: route each task to whichever model is best for it.

The bottom line

Within this matchup, Claude Opus 4.8 remains the one I trust with hard reasoning, science, and agentic coding, and GPT-5.5 remains fast, broadly excellent, and rarely the wrong choice for everyday work. The margin at launch was genuine but small, 61.4 to 60.2, with the real separation on the hard stuff, and that division of labor still holds now that Opus 5 and GPT-5.6 sit above both on the leaderboard. If I could only keep one of the two, I would keep Opus 4.8 by a nose. But I do not have to keep only one, and neither do you.

Put both in the same app and switch per task. See MultiChats pricing and run Opus 4.8, GPT-5.5, and their successors under one subscription, switching whenever the task calls for it.