ChatGPT vs Claude vs Gemini — what does the data say?
In our daily benchmark as of 2026-10-13, Anthropic: Claude Opus 5.5 scores 8.3/10 and OpenAI: GPT-6 Astra scores 7.4/10. Google: Gemini 3.5 Flash Lite leads among the three. We evaluate over 350 models every day, and the result is clear: ChatGPT is not always the best choice for Nordic-language work.
Quick decision
Choose by workflow first, then use the benchmark to check whether today’s model results support that choice.
When the text is long, needs careful editing or must stay strong in Norwegian, Swedish or Danish.
When you need the broadest feature set: files, images, GPTs, integrations and a general-purpose assistant.
When Google Workspace is central to the workday and integration matters more than pure text score.
What does Claude AI cost versus ChatGPT?
Claude and ChatGPT both offer limited free tiers. Claude Pro and ChatGPT Plus are usually around $20 per month.
Paid plans give higher limits, better access to stronger models and more features.
Price is only half the picture. For Nordic-language work, compare language stability, instruction following, document handling and your actual workflow.
Instruction: 10.0/10
Speed: —
Instruction: 10.0/10
Speed: —
Instruction: 10.0/10
Speed: —
How we compare
Every morning, over 350 AI models are evaluated on Scandinavian languages using standardised tasks.
The public page shows practical signals: overall score, language quality, instruction following, speed and price. Exact weighting and task content are proprietary.
ChatGPT: strongest on breadth
ChatGPT has the broadest ecosystem: GPTs, file analysis, image generation and many integrations. Choose it when you need a general-purpose assistant.
Claude: strongest for text and documents
Claude is often the safest choice for longer writing, editing, summarisation and document work in Nordic languages.
Gemini: strongest inside Google workflows
Gemini is most interesting if Gmail, Docs, Drive and Meet are already central to your work.
Price: compare before you pay more
Monthly price says little without quality data. Lower-cost models can sometimes deliver better value.
Who should choose what?
Claude for text, ChatGPT for breadth, Gemini for Google integration, and API models for technical teams focused on cost.
Typical price
| Service | Free | Paid | Price/month | Strength |
|---|---|---|---|---|
| ChatGPT | Limited free tier | Plus / Pro | ~$20+ | Breadth and features |
| Claude | Limited free tier | Pro | ~$20 | Text and documents |
| Gemini | Free Flash | Advanced | Google One | Google integration |
FAQ: ChatGPT vs Claude vs Gemini
Read also
How to get more value from this comparison
Use this comparison 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.