What we tested these two models on, what each test found, and the prices and limits that do not change with the job. The pick changes with the job, so the page starts there.
Aug 25, 2026 · 6 min read
We are not claiming one of these two is the better model. We put them against each other on specific jobs, and the answer changes with the job.
Three of those jobs have a full write-up behind them, and twelve further articles put one of these two models against a different one. The cards below open the three, and the index further down lists all twelve, so nothing here has to be taken on trust. Where the public evidence is thin the page says so rather than filling the gap with a verdict.
What we compared is set out underneath. First the published prices and limits both models bring to any job, then the model-level dimensions where a graded benchmark actually separates them. Those hold whatever you are doing. Which of the two to reach for does not, which is why the jobs come first.
One thing to be clear about before the tables. This page compares the two models through their APIs in one neutral setup. It is not a comparison of the apps around them, so a file upload, a browser plug-in or an IDE integration is not part of anything here.
Neither model wins in general, so this pair is settled one job at a time. Each card names a job we tested, says which model took it and why, and opens the full test behind that answer. The method is the same in all three: one prompt, one setup, and score what comes back before editing it.
Opus 5 first, Sol to render. Opus 5 finds more of the requirements and puts the unresolved decisions in front of you. Sol is the pick when the harder requirement is an exact template or a tight word budget.
Learn moreOpus 5 for the first pass and Sol for the last. Opus 5 handles contradictory accounts better. Sol holds a house template and keeps the level of detail steady across a whole document set.
Learn moreClaude Opus 5. It carries the same completeness and reliability lead into legal drafting that separates the pair on the model-level benchmarks generally. Sol writes the more client-ready prose, so it suits a second pass once the terms are locked.
Learn moreThe published figures both models bring to any job. The last column reads them for the pair rather than for one task.
Figures from Anthropic and OpenAI documentation. Opus 5's prices were re-checked on 25 August 2026, and Sol's on 26 August 2026 - Sol's figures are OpenAI's current promotional rate, not its list price. Anthropic publishes no long-context tier for Opus 5. Fast mode is a separate product at $10 and $50 per million and is not compared here.
The general layer, underneath the jobs above. These are model-level dimensions graded on the exact versions, so they hold whatever the job is. A dimension whose only evidence is task-specific is left to the task pages.
Every Elo above is a maximum-effort row. Opus 5 at medium effort scores 1,469 on AA-Briefcase, below Sol's maximum-effort 1,503, so pick your effort setting before reading the board.
Every article on this site that puts one of these two models under a graded test, grouped by model. The three on this exact pair are the cards higher up the page.
Where else we tested Claude Opus 5
Where else we tested GPT-5.6 Sol
The figures here are the best public evidence on these two exact versions. They are still narrower than the decision you are making.
Every Elo on this page is an effort-dependent row, and the two boards grade broad professional work rather than your document set. This page no longer cites a legal-specific benchmark for the contract-drafting pick, because the figure could not be re-confirmed at its source at review time, so that pick now rests on the same general-purpose boards used everywhere else on this page. None of the boards here grade whether a model will tell you a step is missing instead of filling the gap with something plausible, and both vendors document that failure mode themselves. Prices move, so check them rather than inheriting a figure from a page.
Playgram is not the right buy for everyone either. If one person needs one model and nothing else, a single vendor subscription is simpler and cheaper than a workspace built for a team.
The safest last step is to test the shape of your own material rather than a generic prompt from the internet. A fair test needs the same setup on both sides: the same sources, the same prompt and the same place to run them, so the result reflects the models and not the tool around them. In practice that is harder than it sounds, because most teams end up running one model in one app and the other somewhere else on a separate subscription, which tilts the comparison before the first answer arrives. The cleaner the setup, the more the difference you see is really Claude Opus 5 against GPT-5.6 Sol.
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