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
So the expensive part is often getting from the answer to the accepted results.
so that's an interesting one and now it gets even more complex because tokens were not born equal so by the way the point here is not to not use the agentic tool just to know that in as you said intelligence cost but it gets even more complex because tokens were not born equal and every model lab has its own tokenizer you've just seen the open ai but
Different model labs have different tokenizers.
So, for example, the OpenAI current tokenizer has a vocabulary of about 200,000 tokens.
Gemini has around 256,000.
Lama by Meta has about half of that.
And Claude is unpublished.
And the reason why we all should care is that the price per million tokens is denominated in each lab's own tokens, and often we don't know them.
And the same document can be 10 to 20% more tokens on one provider than another.
And even more so for a code and non-English text.
So the model behavior widens the gap.
And one model may answer in a single pass while another reasons longer and writes more and takes more agentic steps or needs retries.
And the tool around the model adds its own system and context and the loop design.
So the two stacks doing the same task can have different token counts and different completion rates.
And as a result, it's a completely different build.
The per token price is kind of the sticker, but the cost per accepted task is the operating metric, because otherwise there is no way for you to compare between different providers and different tools.
All right.
An important story that also illustrates that, what happened when Opus 4.7 came on board.
The tokenizer basically under the hood changed, and it was this April, and the price sheet was identical to the previous model, the same dollar per million token.
But the model was shipped with a new tokenizer that produced by Entropix on documentation.
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