Every day we run the same tasks on frontier and open-source models, track the cost difference, and tell you the verdict. No hype. Just data.
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We don't benchmark on toy problems. We test the things AI prosumers and developers actually need to do.
LeetCode-style problems and real debugging tasks. Does the $0.89 call beat the $0.03 one?
Long documents condensed. We measure quality and cost — often the cheap model wins.
GSM8K-style problems plus chain-of-thought quality scoring. Not all reasoning costs the same.
"Explain X with citations." Accuracy, depth, and cost — all measured.
Coherence, originality, fluency — and how much you actually need to pay for good output.
Task difficulty: medium | Metric: correct output + tokens used + cost
Verdict: Llama 3.3 70B at $0.004 delivered equivalent output to GPT-4o at $0.089. You don't need to pay 22× more for this task.
One format for quick verdicts, one for the full picture.
Task shown. Models run. Cost delta revealed. Every day, one question answered: is the expensive one worth it?
We replace a $20–200/month AI tool with the cheapest capable alternative for an entire week, then report back with real data.
Results, verdicts, and occasional deep-dives — straight to your inbox.
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