Which AI should you use?
Choose what you need to do, and we point you toward AI models that fit the task — not just the leaderboard.
Choose a task. Get a recommendation.
Takes under a minute. You get one main choice and good alternatives.
Answer four quick questions and get a more precise recommendation with free and lower-cost alternatives.
You do not need an account or payment card to get a recommendation.
One AI is not best for everything.
Some models are strong at language. Others are better at facts, images, code or long analysis.
We ask what you actually want to use AI for.
We show strengths and weaknesses, not just marketing.
You get a recommendation with a reason.
«It is fine to choose a good enough model. You do not need to follow everything.»
Popular models have different strengths.
The homepage can show the differences quickly without exposing internal scoring.
We look beyond benchmark.
Benchmark is useful, but not enough. Everyday use matters too.
Flow, tone and understanding
When precision matters most
Free, paid and API
How easy it is to succeed
The data basis behind the recommendations
Recommendations are based on standardised assessments of quality, language, price, speed and stability. The exact weighting is proprietary.
Ready to find the right AI?
Start the test and get a concrete recommendation based on what you actually need to do.
Start the AI testHow to get more value from this page
Use this page as a practical decision aid, not as an advertising list. HvilkenAI is built to make AI selection easier when the market changes quickly and model names alone say little about real quality.
Start with the task you actually need to solve. A model that is good at short chat is not automatically best for long documents, code, customer-facing text, research or work involving sensitive information. Consider language quality, price, speed, stability and how much editing the answer requires before choosing a subscription or API.
We evaluate over 350 AI models and present the most useful signals in a format that works for everyday users, students, businesses and developers. The exact calculation is proprietary, but the assessment is based on standardised tasks, updated benchmark data and editorial review of whether the recommendations make sense in practical use.
For important decisions, run a small test of your own: use the same prompt, language and expected format in two or three relevant models. Look at precision, source handling, tone, speed and how easy the answer is to verify. That makes the benchmark a time-saving starting point, not a final answer you must follow blindly.
Use the links on the page as well. One page rarely gives the whole picture: the benchmark shows today’s numbers, the AI test translates your need into concrete recommendations, and the privacy/terms pages explain which data and limitations you should consider. Used together, these sources make the choice more robust than following a model name from social media.
If the result will be used at work, document why the tool was chosen: which task it solves, which alternatives were considered, which data should not be shared and how the answer will be quality-checked. That makes it easier to switch model later if price, quality or provider terms change.
When a page is included in the sitemap, it should also stand on its own as a useful explanation. That is why we emphasise practical choices, concrete control questions and clear limits for how data can be used.
The goal is that the reader can move on with a safer choice after a few minutes, without already knowing every model or provider.
Pay particular attention to whether the recommendation fits the language, price and risk in your own situation.
In short: choose what you can verify.
When free is enough
Choose free or low-cost first when the task is simple, risk is low and you can verify the answer yourself.
When paid is worth it
Paid models can be worth the cost when documents are long, precision matters or you save real working time.
When to wait
If the need is unclear, start with the test and benchmark before committing to a provider.