Nufar Gaspar
speaker
2,488 appearances
11 recordings
1 series
first heard Oct 2025
last heard 3 Sep
Nufar Gaspar’s voice in public audio — every appearance, attributed to the second.
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recordings per month · last 12 monthsRecordings per month over the last 12 months — 11 in all, peaking in Jun 2026 with 5.
Appearances
That's the second layer.
These are the tokens being used for the model internal thinking before answering.
For the most part, it's going to be invisible to you, but it's billed at the output rates, meaning at the high rate of per token cost.
And those can add between 4 to 20x cost per request.
And finally, we have the output.
That's the answer that you actually see.
And this is typically 3 to 5x more expensive than the input price per token.
And I think the reasoning layer is the one layer that catches everybody by surprise.
Because you might have a 400 token answer, but under the hood, it carried like, I don't know, 4,000 thinking tokens underneath because the model was having an internal monologue and doing a lot of thinking in order to give you the answer.
And if you want the analogy, it's like thinking about the part of the restaurant bill that is labeled the kitchen time.
So you don't get to see it.
It's not part of the dish, but you still have to pay a lot of it for that.
And the models with the high reasoning effort are often the one with the 20x amount of tokens being consumed versus the lower reasoning effort.
It can be the same question with a significantly different price tag.
And sometimes spending a higher reasoning does not get you better results.
So
Some metrics even showed that for a simple question, it's better to use lower reasoning because the overall cost per task will be significantly lower and the quality will be improved without having the model overthink everything.
So it's not always that smarter or spending more time thinking gets you better results.
Right.
And I think that the gap between input and output pricing keeps widening at the frontier.
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