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实时 23:01:17
English(EN) Well, I found how to use all my (unified) RAM, at last. Yes that's ollama running two models (Qwen3.6 (21GB) and llama3.3 (42GB)), pi-dev and opencode. And gues

用户同时运行多个 AI 模型,面临编码任务失败

一位用户分享了他们使用 Ollama 在系统上同时运行多个 AI 模型(包括 Qwen3.6Llama 3.3)的经验。尽管成功利用了内存,但用户指出该设置在处理特定编码任务时仍遇到困难,未能生成所需的用于伽马射线光谱分析的 Python 脚本,并错误地声称其存在。 AI

排序理由 这是一个关于运行 AI 模型的个人轶事,而非重要的行业事件或发布。

在 Mastodon — mastodon.social 阅读 →

AI 生成摘要 · Google Gemini · 来自 1 个来源。 我们如何撰写摘要 →

用户同时运行多个 AI 模型,面临编码任务失败

报道来源 [1]

  1. Mastodon — mastodon.social TIER_1 English(EN) · [email protected] ·

    Well, I found how to use all my (unified) RAM, at last. Yes that's ollama running two models (Qwen3.6 (21GB) and llama3.3 (42GB)), pi-dev and opencode. And gues

    Well, I found how to use all my (unified) RAM, at last. Yes that's ollama running two models (Qwen3.6 (21GB) and llama3.3 (42GB)), pi-dev and opencode. And guess what? It still can't vibe-code and write a simple python script to analyze gamma-ray spectra to the current directory,…