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docs(yutori): drop vendor benchmark + pricing numbers from README
Specific bench scores and per-token pricing will stale fast and aren't load-bearing for the template.
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pkg/templates/python/yutori/README.md

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This Kernel app implements a prompt loop using Yutori's Navigator n1.5 with Kernel's Computer Controls API.
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[Navigator n1.5](https://yutori.com/blog/introducing-n1-5) is Yutori's pixels-to-actions LLM that predicts browser actions from screenshots. Yutori reports **94.5% on Online-Mind2Web** and **88.0% on Navi-Bench v2** at **$1.50 per 1M input tokens** — currently among the most accurate and cost-effective computer-use models.
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[Navigator n1.5](https://yutori.com/blog/introducing-n1-5) is Yutori's pixels-to-actions LLM that predicts browser actions from screenshots.
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This template runs n1.5 in **computer-use-only mode**. n1.5 also supports a hybrid vision + DOM/JavaScript path (page-state extraction, custom JS, structured JSON output) for multi-field forms and bulk data extraction, but those tools are intentionally disabled here — see [Disabled tools](#disabled-tools).
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pkg/templates/typescript/yutori/README.md

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This Kernel app implements a prompt loop using Yutori's Navigator n1.5 with Kernel's Computer Controls API.
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[Navigator n1.5](https://yutori.com/blog/introducing-n1-5) is Yutori's pixels-to-actions LLM that predicts browser actions from screenshots. Yutori reports **94.5% on Online-Mind2Web** and **88.0% on Navi-Bench v2** at **$1.50 per 1M input tokens** — currently among the most accurate and cost-effective computer-use models.
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[Navigator n1.5](https://yutori.com/blog/introducing-n1-5) is Yutori's pixels-to-actions LLM that predicts browser actions from screenshots.
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This template runs n1.5 in **computer-use-only mode**. n1.5 also supports a hybrid vision + DOM/JavaScript path (page-state extraction, custom JS, structured JSON output) for multi-field forms and bulk data extraction, but those tools are intentionally disabled here — see [Disabled tools](#disabled-tools).
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