this post was submitted on 15 Sep 2026
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I found One Million Tokens. Its rough scale:

1M tokens
~ 750K words
~ 3,000 pages
~ 83 hours of conversation
~ 75K lines of code

🧠 The more interesting part is the timeline.

It starts with GPT-3 at 2,048 tokens in 2020, then walks through ChatGPT 4K, GPT-4 32K, Claude 100K, Gemini 1M, and the later multi-million-token era.

The visual change is kind of absurd when you see all the pages stacked together.

One caveat: maximum context is not the same as perfect memory/retrieval. A model accepting 1M tokens can still fail to use information buried inside that window.

The line-of-code/page conversions are approximations too. I am curious how people here design around 1M+ context in practice.

Do you actually feed giant source sets directly, or still prefer retrieval + smaller focused contexts for cost/attention reasons?

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[–] ms_lane@lemmy.world 1 points 2 days ago

I can also show you what 1 Million tokens looks like, behold:

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