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awesome-japanese-llm

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日本語LLMまとめ - Overview of Japanese LLMs

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awesome-japanese-llm

Added 1 June 2026

#foundation-models #generative-ai #generative-model #generative-models #japanese #japanese-language #japanese-language-model #japanese-llm

Overview

A community-maintained GitHub repository that curates a comprehensive overview of Japanese large language models. It organizes models by type, size, and capability, providing links and summaries for developers to compare and select appropriate LLMs for Japanese-language tasks.

Best for

Best for
Developers and researchers seeking a curated starting point for Japanese LLM selection

Use cases

  • Discovering Japanese LLMs for text generation or translation
  • Comparing model sizes and architectures for deployment decisions
  • Finding pre-trained models for fine-tuning on Japanese datasets

Notes

A community-maintained GitHub repository that curates a comprehensive overview of Japanese large language models. It organizes models by type, size, and capability, providing links and summaries for developers to compare and select appropriate LLMs for Japanese-language tasks.

1,407 stars on GitHub. Last updated 2026-05-30. Licensed Apache-2.0.

Use cases

  • Discovering Japanese LLMs for text generation or translation
  • Comparing model sizes and architectures for deployment decisions
  • Finding pre-trained models for fine-tuning on Japanese datasets

Pros

  • Centralized, up-to-date list of Japanese LLMs from multiple sources
  • Community-driven with 1407 stars indicating active interest and contributions
  • Written in TypeScript, making it accessible for web-based tooling

Cons

  • Not a tool itself; requires external model access or hosting
  • May lack detailed performance benchmarks or evaluation metrics
  • Relies on community updates, so some entries could become outdated

Indexed from awesome-llm and enriched against its public facts.

Pros

  • Centralized, up-to-date list of Japanese LLMs from multiple sources
  • Community-driven with 1407 stars indicating active interest and contributions
  • Written in TypeScript, making it accessible for web-based tooling

Cons

  • Not a tool itself; requires external model access or hosting
  • May lack detailed performance benchmarks or evaluation metrics
  • Relies on community updates, so some entries could become outdated