Local vs cloud voice dictation: the complete comparison

Local voice dictation sounds like the obvious choice for privacy: nothing leaves your computer. It is a real advantage, but it comes with trade-offs that rarely make the headlines. Local dictation is slower, it needs a powerful machine, and above all it cannot clean up your text the way modern AI does. Cloud voice dictation sends your audio to a server, which is exactly what makes the AI cleanup possible. The good news: a serious cloud service can give you that cleanup and keep your data private. This guide compares both approaches honestly.

What "local" and "cloud" dictation actually mean

• Local (on-device) dictation: everything runs on your own computer. Your audio never goes online. This covers Apple Dictation in its on-device mode, and Whisper run locally through tools like Whisper.cpp, MacWhisper or the local mode of apps such as Superwhisper.
• Cloud dictation: your audio is sent to a server that transcribes it and, crucially, can run a large AI model to turn the raw transcript into clean text. Services such as Wispr Flow and Fast Dictate work this way, which is why they return punctuated, structured, ready-to-use text instead of a word-for-word stream. They differ in where and how they handle your data, which is the part worth comparing.

Local vs cloud: the comparison at a glance

The privacy argument: local's real strength

Let's give local its due. When dictation runs entirely on your machine, your audio never touches the internet. For highly sensitive material, that is a genuine benefit and the strongest reason to consider a local setup.

But "cloud" does not have to mean "your voice is stored somewhere forever". A serious provider answers the privacy concern directly:

• Zero data retention on every plan: your audio is transcribed and immediately discarded. Nothing is kept, nothing is reused to train models.
• A clear jurisdiction: on the Pro plan, your data is processed exclusively in France, under the GDPR, rather than on servers governed by foreign surveillance laws.

The catch nobody mentions: local cannot clean up your text

This is the part that gets glossed over. Running Whisper locally gives you a transcription, but a transcription is not finished text. It is word for word, with your hesitations, repetitions and false starts left in, and no real punctuation or structure. To turn that into clean, usable text, you need a second model behind the transcription: a large language model that adds punctuation, fixes grammar, removes fillers and respects formatting instructions.

And that is where local runs into trouble on a normal computer:

• The good cleanup models are heavy. Running a capable cleanup model alongside transcription is impractical on typical consumer hardware. You can shrink a model through quantisation to make it fit, but you trade away the accuracy that made it worth using in the first place.
• Smaller models break the formatting. The lightweight models that fit comfortably tend to ignore instructions and produce messy, inconsistent text. They are not reliable enough to trust.
• The models that work best need datacenter GPUs. A consistently reliable result means running large models that are hard to host on a personal machine, and running them anyway tends to be too slow to dictate in real time.

The practical conclusion: on a typical home PC, reliable AI post-processing stays hard to reach. In most local setups, dictation gives you a raw transcript that you finish by hand. That is the opposite of what most people want from voice dictation.

Speed and hardware

Even before the cleanup question, local transcription can be demanding. The small Whisper models run on a CPU, but accuracy and speed are limited; the large-v3 model, which gives the best results, really wants a dedicated GPU to run at a comfortable pace. On a standard laptop without a strong graphics card, the heavier models fall back to the CPU and quickly become slow. Running transcription and a language model at the same time pushes even high-end consumer hardware to its limits.

Cloud dictation moves all of that off your machine. The heavy work happens on servers built for it, so dictation stays fast on any computer, including a light laptop with no dedicated GPU. You are not buying or maintaining hardware to get a clean result.

So which should you choose?

Choose 100% local if you must work completely offline, you only need a raw transcript, you own a powerful machine with a strong GPU, and you are willing to edit the text yourself afterwards.

Choose cloud dictation if you want clean, punctuated, ready-to-use text instantly, on any computer, in any application, without buying hardware, and with your privacy protected by zero retention, plus France-only processing on the Pro plan.

Fast Dictate: cloud done right

Fast Dictate is built to give you the benefits of cloud dictation without the privacy compromise:

• The full pipeline: accurate transcription plus a large AI model that cleans up, punctuates and structures your text.
• Works everywhere: Word, Gmail, Notion, your browser, any text field, with a single shortcut on Windows and Mac.
• No hardware needed: fast on any computer, no GPU required.
• Privacy by design: zero data retention on every plan; Pro processed exclusively in France.
• Pro plan: data processed exclusively in France on ISO 27001 servers, advanced GDPR DPA, for confidential work.
• Free plan: 2,000 words per week, no credit card.

Frequently asked questions