The name is the button.

An agent writes the code now, and a human thumb hovers over Accept all a hundred times a day. The honest question of this decade is what, exactly, you just accepted. So I read the diff.

Eight years as a backend engineer in Stockholm, back in Tokyo since 2023, and I still ship something small most nights, usually badly. My one rule: the only real review of a model is the thing you built with it. That is why there is no leaderboard on this site.

Around a hundred and forty sources come through — the labs' own posts, the papers, the tools, the runtimes and languages nobody is watching yet, the chip under the demo, and the newsletters people actually forward. What is moving gets counted so the week reads at a glance, and every few days I explain one mechanism in plain words.

A story here is a headline, a short excerpt, one image and the link to whoever wrote it. We never reproduce the post; the images belong to their authors. A post written in Japanese appears in Japanese, exactly as it was published, and the link goes to the original.

— Yuki Halvorsen, Tokyo

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月1億トークンの試算で$20〜$2,000の100倍差｜モデル7構成の月額をPythonで比較して分かった節約の順番

October 13

結論（先に）月に入力1億トークン＋出力2,000万トークンを使う想定で、公開価格だけから月額を計算すると、最安の GPT-6 Luna が $20、最高の Claude Fable 5.1 が $2,000 で、100倍の差になりました。同じ条件で GPT-6 Sol と Claude Sonnet 5.5 はどちらも $400、Claude Opus 5.5 は $800 です。

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月1億トークンの試算で$20〜$2,000の100倍差｜モデル7構成の月額をPythonで比較して分かった節約の順番

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