HyperWhisper doesn’t lock you into one engine. It ships a library of models because no single model wins on everything — each trades off privacy, language coverage, speed, accuracy, and cost differently. This page lists everything on offer and explains why each one is there. There are two kinds of model:

• Speech-to-text — turns your voice into text (the transcription step).
• Post-processing — an optional LLM pass that cleans up, punctuates, and formats the transcript afterwards.

You choose both in the app under Model Library, and per-mode in the mode editor.

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Three ways to run a model

Every model — speech or post-processing — falls into one of three buckets:

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Speech-to-text models

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On-device

These run locally with no network calls. Once downloaded (where applicable) they work fully offline — your audio is never uploaded anywhere. See Data Privacy for details.

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Whisper models

OpenAI’s general-purpose multilingual models. The VRAM values are the recommended GPU memory for full acceleration — with less, the model still runs on CPU (or partial GPU), just slower.

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NVIDIA Parakeet models

NVIDIA Parakeet models are typically faster than equivalent-size Whisper models and very accurate for the languages they support. Parakeet V3 covers: English, German, Spanish, French, Italian, Portuguese, Dutch, Polish, Russian, Ukrainian, Czech, Slovak, Hungarian, Romanian, Bulgarian, Croatian, Slovenian, Serbian, Danish, Swedish, Norwegian, Finnish, Estonian, Latvian, Lithuanian.

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NVIDIA Nemotron 3.5 models

NVIDIA’s Nemotron 3.5 ASR is the newest on-device option (macOS). It edges out the other local models on accuracy and reaches well beyond European languages — the multilingual variant is the only local model that handles Chinese, Japanese, Korean, and Arabic.

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Apple Speech & Qwen3 ASR

• Apple Speech is built into macOS — no download, available the moment you launch the app. It’s the quickest private option for everyday Mac dictation. (Requires a recent macOS version.)
• Qwen3 ASR is an additional multilingual on-device model (macOS) for users who want to try Alibaba’s ASR.

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Offline language coverage at a glance

Not sure which local model handles your language? This table maps the common use-cases. For the full Parakeet V3 and Nemotron language lists, see the sections above.

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HyperWhisper Cloud

HyperWhisper Cloud is built-in — no API key, no separate account. It routes to best-in-class providers behind four accuracy tiers, and you only pay for actual speech (silence and empty recordings cost 0 credits). Use it when you want the highest accuracy without any setup. See Providers for pricing, cost examples, and per-language guidance.

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Bring your own key

If you already hold API credits, want a provider’s free tier (Deepgram $200, AssemblyAI $50), or need a specific model, plug in your own key under API Keys. You pay the provider directly at their published rate. Supported providers for bring-your-own-key transcription: OpenAI · Groq · Deepgram · AssemblyAI · ElevenLabs · Mistral · Soniox · Google Gemini

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Post-processing models

Post-processing is an optional second step: after transcription, an LLM cleans up filler words, fixes punctuation and capitalization, and applies any formatting your mode asks for. It’s separate from the speech model — you can mix any speech model with any post-processing model.

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Cloud post-processing

Available built-in through HyperWhisper Cloud (no key needed) or with your own API key. Every cloud post-processing model is labeled with a speed and accuracy rating (explained in the Rating scale section below) so you can pick the trade-off that matters to you.

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Local LLM post-processing

Local Gemma 4 models clean up and format transcript text fully offline after download — your text never leaves your device. The local LLM is powered by a bundled llama.cpp server that starts automatically when the mode needs it. Platform availability:

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Rating scale

Every model in the library — speech-to-text and post-processing — shows a Speed bar and an Accuracy bar, each rated 1–5. The numbers come from an internal benchmark suite run over real recordings (results in benchmarks/results/). The Model Library sorts by the sum of Speed + Accuracy (descending) so the most balanced models float to the top. If you care more about one dimension than the other, you can scroll past the top recommendations to find a model that emphasizes speed or quality specifically.

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Using on-device models

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Downloading & storage

Open Model Library in the app, click Download on any entry, and watch the circular progress indicator. You can cancel mid-stream with the × button. Downloaded models stay on disk until you remove them. Apple Speech is built into macOS and needs no download.

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GPU vs CPU

Local engines use your GPU when available and fall back to CPU automatically if you don’t have a dedicated GPU or there isn’t enough VRAM. The model still runs on CPU — it’s just slower.

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Removing models

To free up disk space, click the trash icon next to any downloaded model in Model Library. The file is removed immediately and can be re-downloaded any time.

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Which should I pick?

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Boost accuracy on any model

• Custom vocabulary — add product names, jargon, and colleagues’ names. The single biggest improvement for technical or professional use. (Support varies by model — Apple Speech and Whisper support it locally; among cloud providers most do, a few don’t.)
• Low-noise environment — every model degrades with background noise. See Best Practices.
• Natural pace — speech that’s too fast or too slow both hurt accuracy.

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Go deeper