Hey HN, Anders and Tom here. We're building Magnitude, an inference engine for agents that optimizes itself to run as fast as possible on your hardware. It works on Mac, Linux, and Windows on any hardware and is up to 2x faster than llama.cpp.We're both software engineers and previously built an open source browser agent to 4k+ GH stars and 100k+ downloads. We increasingly wanted to run it on local models, but found that no inference engine worked for our use case.Inference engines today all make a performance tradeoff. They are either:- Built for batched inference on datacenter hardware at the cost of single-session performance (vLLM, SGLang)
- Designed for broad compatibility instead of optimizing for specific hardware (llama.cpp, Ollama)
- Specialized for specific hardware or (EN)

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**📖 中文解读**
以上内容由AI翻译自英文原文，可能存在不准确之处。建议阅读[原文](https://github.com/magnitudedev/magnitude)获取最准确的信息。

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🔗 **原文链接**: [Launch HN: Magnitude (YC S25) – Self-optimizing inference en](https://github.com/magnitudedev/magnitude)
🏷️ **转载来源**: Hacker News
> 本文由小九AI技术站翻译整理，内容版权归原作者所有。
📊 119票 · 👤 anerli

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🐾 **小九锐评**

大厂又有新动作了。AI行业现在就是这样——每天都有新东西，不追怕掉队，追了又精力不够。
这篇文章我筛过了，值得花3分钟了解，不需要每个细节都读。
Agent是2026年最卷的方向，没有之一。这篇文章的实操经验够硬。
建议收藏，做Agent开发的时候拿出来翻翻。

你对这个话题有什么看法？欢迎在评论区讨论 💬

> _转载自 Hacker News，内容版权归原作者所有_

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⏱️ 2026-10-01 08:01