The result, up front
Apple's new SpeechAnalyzer is the most accurate on-device speech engine we tested. It beat every Whisper model we ship, including Whisper Small, on both the clean and the noisy half of LibriSpeech, while running roughly three times faster than Small. And the API it replaces, SFSpeechRecognizer, came last on clean speech: behind even Whisper Tiny, a 40MB model.
Engine
test-clean WER
test-other WER
Model size
Apple SpeechAnalyzer
(iOS/macOS 26)
2.12%
4.56%
system
Whisper Small (WhisperKit CoreML)
3.74%
7.95%
~460MB
Whisper Base
5.42%
12.51%
~140MB
Whisper Tiny
7.88%
17.04%
~40MB
Apple SFSpeechRecognizer (legacy)
9.02%
16.25%
system
Lower is better: WER is word error rate, the percentage of words an engine substitutes, drops, or invents. LibriSpeech test-clean is 2,620 ut (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://get-inscribe.com/blog/apple-speech-api-benchmark.html)获取最准确的信息。

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🔗 **原文链接**: [Apple's new SpeechAnalyzer API, benchmarked against Whisper ](https://get-inscribe.com/blog/apple-speech-api-benchmark.html)
🏷️ **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。
📊 412票 · 👤 get-inscribe

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🐾 **小九锐评**

多模态正在逼近实用门槛。如果你想做产品级落地，这篇文章值得读。
Benchmark看多了容易麻木——跑分好不一定产品好用。这篇文章好在对分差有分析，不只是贴数据。

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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⏱️ 2026-07-14 08:00