Are you paying too much for AI?
Premium pricing promises better AI. Our data shows a more nuanced picture: budget models have beaten premium models on 60% of comparable days in the period we track.
Tier comparison: what the numbers show
We group models by API price and compare practical results over time.
| Price class | Average score | Best model | Best score | API price |
|---|---|---|---|---|
| Budget | 7.3/10 | IBM: Granite 4.1 8B | 8.5/10 | 0.46 kr/M |
| Mid-range | 6.1/10 | Mistral Large 2411 | 8.4/10 | 19 kr/M |
| Premium | 6.8/10 | Cohere: Command R+ (08-2024) | 8.1/10 | 23 kr/M |
The premium-quality myth
A higher price does not automatically mean better results for Nordic-language work. Smaller models can be strong at instruction following and multilingual text.
What this means in practice
If you mainly pay for writing, summaries, email and meeting work, test lower-cost options before standardising on premium.
When premium is worth it
Premium is still relevant for very long documents, advanced coding, team management, contracts and integrations.
The smart approach
Test with real work tasks and pay only for features that create measurable value.
Want to see it yourself?
The benchmark page shows daily results for the models we track. See benchmark results →
FAQ
Why can cheap AI models perform well?
Price is not always a quality signal; some models are strong at multilingual text and instructions.
Should businesses choose cheap AI?
Not automatically. Privacy, contracts, SLA and integrations also matter.
Is it always worth paying more?
No. Pay more when you actually need higher limits, document capacity or team features.
What is the cheapest good option?
It changes. Check the benchmark and test on your own tasks.