Which AI Is Best at Math? The Honest Ranking
By Chatday Editorial Team ·
If you want the AI that’s strongest at math right now, it’s GPT-6.1 Sol. Earlier this month it became the first model to solve every problem in the hardest tier of FrontierMath, a test built from research-level questions that professional mathematicians write and that AI couldn’t touch until recently. Claude Sonnet 5.5 and Claude Opus 5 come next among the models you can actually use in Chatday.
That’s the leaderboard answer. For a fraction worksheet, a mortgage estimate or a tip split, though, any of the top models will get you there, and the mistakes they still make have little to do with how clever they are.
How we ranked the AI models for math
We didn’t invent a test. We leaned on the toughest public one: FrontierMath, run by the independent research group Epoch AI. Its hardest tier is a few dozen unpublished problems at the level of real mathematical research. The answers aren’t on the internet, so a model can’t have memorized them.
We picked it for three reasons:
- It’s hard enough to separate the top models. Easier school-level tests stopped telling them apart a while ago, because they all score near the top.
- It’s checked automatically. The model has to give an exact final answer, so there’s no grading on vibes.
- It’s independent of the companies. Mostly. More on that in a moment.
Then we kept only the models Chatday actually serves, so every name below is one you can open and try today.
The ranking: which AI is best at hard math
Here’s how the models available in Chatday did on FrontierMath’s research tier, translated from percentages into something easier to picture. Scores are from the public leaderboard as of mid-October 2026.
| Model | Research-level problems solved | Best for |
|---|---|---|
| GPT-6.1 Sol | All of them | The toughest proofs, puzzles and multi-step problems |
| Claude Sonnet 5.5 | About 8 in 10 | Hard math explained in calm, readable steps |
| Claude Opus 5 | About 7 in 10 | Long problems where you want careful reasoning |
| GPT-5.5 | About 7 in 10 | A solid, familiar all-rounder |
| Claude Haiku 5.5 | Almost half | Quick help when speed matters more than depth |
| Grok 4.6 | About 1 in 3 | Everyday questions, not competition math |
| Gemini 3.1 Pro | About 1 in 4 | Mixed tasks like reading a chart or a photo of a worksheet |
A few things jump out.
GPT-6.1 Sol is the surprise winner. It isn’t even OpenAI’s most expensive model. It’s the cheaper tier that OpenAI launched at its DevDay on September 29, and it matched, and by a hair beat, the company’s own flagship on this test. We covered the launch in our GPT-6.1 Sol explainer.
Claude is the strong second family. Sonnet 5.5, the mid-size Claude, actually scored a little higher than the bigger Opus 5. Newer beats bigger here, which is a useful reminder that a model’s name doesn’t tell you its rank.
Gemini and Grok fall behind on this specific job. That doesn’t make them bad. Gemini 3.1 Pro is built for mixed tasks, like reading a photo of a problem, and Grok is quick and chatty. They just aren’t the ones to hand a really hard proof.
Why a model that aces research math can still fumble your homework
This is the part that catches people out. A model that can crack research-level problems can still flub something as plain as 17% of 240 if it rushes. (It’s 40.8, by the way.)
The reason is how these models read. They don’t see numbers the way a calculator does. They break text into chunks and predict what comes next, which is also why some of them can’t count the R’s in strawberry. Long chains of digits are exactly where that can slip.
Wording matters too. In 2024, Apple researchers tested models on grade-school word problems and added one harmless-sounding but irrelevant sentence, something like a note that a few of the apples were smaller than the rest. Scores dropped sharply, by as much as 65% for some models, because they tried to use the extra detail. Later re-tests on newer models found a much smaller effect, so the gap has narrowed a lot. The lesson still holds: the trickiest part of a word problem for an AI is often the reading, not the math.
Here’s where everyday mistakes usually come from:
| What goes wrong | What it looks like | The quick fix |
|---|---|---|
| Rushed arithmetic | A wrong digit in a long multiplication | Ask it to redo the calculation step by step |
| Misread question | Answers “per month” when you asked “per year” | Restate the question in your own words first |
| Red-herring details | Uses a number that doesn’t matter | Tell it which facts are relevant |
| Overconfidence | A clean, wrong answer with no doubt | Ask how it would check the answer |
Best AI for math, by what you’re actually doing
The leaderboard tells you who’s smartest. This tells you who to open.
Best for a student stuck on homework
Use Claude Sonnet 5.5. It’s near the top on hard math and tends to explain each step in plain language, which is what you want if the goal is to understand it rather than copy it. Ask it to give hints before the answer. Our prompts for homework help are built around that idea.
Best for genuinely hard problems
Use GPT-6.1 Sol. Olympiad puzzles, a proof you can’t crack, a statistics question with five moving parts. Give it time to think and ask for the full working.
Best for money math
Budgets, loan repayments, splitting rent. Any top model works, so pick the one you like talking to. The risk here is a single wrong digit, so always ask for the working and sanity-check the final number yourself.
Best for a photo of a worksheet
Gemini 3.1 Pro is built to work with images as well as text. Let it read and transcribe the problem, then hand the actual solving to GPT-6.1 Sol or Claude if it’s a tough one.
How to get math answers you can trust
You don’t need a special prompt. You need three habits:
- Ask for the steps, not just the answer. “Show your working” makes the model slow down, and it gives you something to check.
- Make it verify. Follow up with “Plug your answer back into the original problem and check it.” It’s a cheap way to make a slip show up.
- Get a second opinion. A different model makes different mistakes, so agreement between two of them is worth a lot more than one confident reply.
That last habit is the reason it helps to have several models in one place. Asking GPT-6.1 Sol and then Claude Sonnet 5.5 the same question shouldn’t mean two apps and two subscriptions.
Try the top two side by side
Want to see the difference on your own problem? Pick a question you actually care about, a tricky homework item or a calculation you’d rather not get wrong, and put the two strongest math models next to each other.