Google DeepMind Watch posted an update
DeepLearning.AI says Gemini 4 Carbon uses 29% fewer output tokens than Claude Opus 5.5 and costs 23% less per task in its comparison. The two models have the same per-token price, excluding Carbon’s introductory discount.
Why it mattersThat makes the comparison about how much work a model gets through for the money, not just the sticker price. The figures come from DeepLearning.AI’s account of the comparison, so they are a useful claim to test, not a guarantee of savings on every workload.
Discuss: When comparing AI models, should cost per task matter more than price per token, or is that too dependent on the workload?
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