I've dictated over 120,000 words with my voice - these are my 3 favorite tools (and one is free)
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Since February, I have dictated 120,896 words. In the last three months alone, I have dictated 50,234 words. I've done this across 2,314 individual microphone recording sessions, averaging about 24 words per dictation sequence.
With improvements in AI, dictation quality, speed, and accuracy have come a long way. Over the years, I've tried to work with speech recognition many times, but it hasn't been very successful until quite recently.
A typical article is roughly a thousand words. So if you look at it that way, I have dictated the equivalent of roughly 120 articles since February.
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That's not to say I don't type. I type a lot, but it's clear that I also use dictation a lot . I've adopted voice dictation as a primary input modality for two key reasons. First, it helps to protect my wrist, which tends to have carpal tunnel symptoms . By dictating, I'm using my wrist a little bit less.
In this article, I'll show you the three primary contenders that I've looked at and spent time with this year. I'm also going to go over a number of also-rans and honorable mentions, just to give you an idea of the dictation tools that are out there and how they differ.
When it comes to dictation products, there are a variety of factors to consider. Price is certainly one of them. But there's also the question of whether or not you want your words sent up to the cloud to be processed or whether you want to keep them private and local.
Accuracy is another factor to consider. Back in the day, it used to be much more of a problem. Fortunately, the voice models have achieved a level of overall quality that allows basic English words to be transcribed quite accurately. Some of the dictation products support other languages, but since I work only in English (at least for human languages), that's what I'm covering in this article.
You also need to be able to correct your words as you're dictating. Some AIs go back and clean up mistakes you've made and provide you with clean text in whatever it is you're dictating into.
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I am dictating most of this article just as a proof of concept to make the point that an article can be dictated. But that's not the norm for me. Despite all the dictation I do, I don't usually dictate my articles. I sometimes dictate a few lines of an article, but mostly I type them out.
One of the reasons I don't use voice dictation for my articles is that voice dictation isn't particularly good at formatting. It's quite good at just laying down text, but if you want to arrange something, create a table, create bullets in a certain format, have indented quotes, or add any of the physical artifacts of an article, you have to go back and do that by hand after you dictate.
Because of the regular need to do editing and superfine word crafting, I don't find voice dictation to be nearly as effective as hand typing on a keyboard like a caveman.
On the other hand, I use voice dictation a lot when working with Claude Code or OpenAI's Codex to vibe code any of the products I'm working on. I use it a lot in Slack and Google Chat when talking to my editors and some of my project partners.
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I use voice dictation quite a lot when replying to email messages. I use it a little bit less when composing new messages, but I use it there sometimes as well. I use it a lot when taking notes. I also use it sometimes for search phrases in Google or prompts that I give to ChatGPT, Gemini , or Claude Code.
(Disclosure: Ziff Davis, ZDNET's parent company, filed an April 2025 lawsuit against OpenAI, alleging it infringed Ziff Davis copyrights in training and operating its AI systems.)
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I find that voice dictation is sometimes a little bit less precise and a little bit less disciplined than writing each word with the keyboard. But I can dictate at an average of 118 words per minute, while my typing is usually in the 70- to 80-word-per-minute range.
When I'm working on an article, I sweat each sentence, choosing the words and structure with great care. Typing lends itself to that kind of attention to detail.
But when I'm vibe coding, for example, and I'm discussing how I want a feature to be instantiated, how I want something to behave, or a bug that I've noticed, speaking is considerably faster and also considerably more gentle on my hands than typing it into the computer.
I find two features to be mission-critical. The first is a customizable dictionary, so that when I say something like ZDNET, the dictation product understands how I want it spelled and presented.
The second is an on-the-fly correction capability, so that when I say something and then correct myself and re-say it, the version that lands in whatever I'm dictating into contains those corrections.
One oddly missing feature in all of the voice dictation products is the ability to go back and selectively edit already pasted-in words. Nothing can do this except the native Mac Voice Control or Windows Voice Access that comes with the operating systems themselves. Unfortunately, those two capabilities often conflict with the voice dictation products in inconvenient ways, so they don't combine well as integrated solutions.
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Almost all the dictation products are initiated by a hotkey. I bind the dictation hotkey to a button on my mouse so that when I tap the button, the dictation starts or stops. This allows me to dictate regardless of what application or web page I'm in at the moment. It means I can do computer input even if my keyboard isn't in front of me.
In addition to the simple ability to listen to speech and turn that into typed words, most of the dictation products come with a dizzying array of configuration options, specialty features, and computer command capabilities. For example, some specialize in post-processing dictated speech with an AI for specific applications, like auto-formatting email messages. Others have features like transcribing an audio file. And nearly all of them give you some choice over what language model is being used for the dictation processing.
I'm not going to spend much time on those bells and whistles in this article. Instead, I'm going to focus on the most important aspect, which is how well the tools turn speech into written text. To that end, I will be spotlighting three products: Wispr Flow , Superwhisper , and FluidVoice. That's next.
At $144 a year, or $15 a month, Wispr Flow is certainly not cheap, but I would argue it's actually worth it. Despite trying almost all the other products, this is the one I keep coming back to and have used more than any other.
Wispr Flow is the only one of our top three available for Mac, Windows, iOS, and Android. It is not, however, available on Linux, although the company has a waitlist for Linux users.
Wispr Flow's standout feature, at least in terms of my usage, is its in-flight self-correction. As you're dictating, you can correct yourself, and it updates what's being transcribed. Once you get used to this feature, you really don't want to go back, especially if you're doing a large amount of dictation like I do.
It means that the text you produce is, more often than not, usable because if you misspeak, you can fairly easily correct it as you're speaking and end up with a decent result.
None of the other models that I tested were able to do this as smoothly. Some couldn't do it at all. FluidVoice has come close, but I would say that Wispr Flow made accurate corrections eight out of 10 times, and FluidVoice made accurate corrections maybe four out of 10 times. For in-flight self-correction, that's measurable when you're doing a lot of work.
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I also found that Wispr Flow's dictionary is reliable and effective. What I mean by that is that once I've trained it on an incorrectly spelled word or incorrectly interpreted word, I almost never have to go back and correct it again. Once I trained it on the word ZDNET, for example, Wispr Flow reliably gets it correct just about 100% of the time. That's also the case with my library of 90 or so other words that I regularly correct.
Wispr Flow has two dictionary options: It allows you to feed it individual words like Gewirtz, and it allows you to feed it misspellings or misinterpretations and then the corrected word. For example, it regularly had trouble with the word Claude, which it would represent as "call it." I set up a dictionary definition for "call it code" that converted to Claude Code, and I've never had a problem since.
Once in a while, Wispr Flow misses the insertion of a chunk of text into the destination location. For example, I might dictate a paragraph that I want to go into Notes, and it never winds up there. Wispr Flow keeps a history of dictation in its app. If it misses insertion, I can open it up in the app, copy from the history, and paste it in. I don't ever actually lose any of my dictation, even if it doesn't always arrive on target the first time out (which is a fairly rare occurrence).
Beyond price, my biggest concern about Wispr Flow is that it's a cloud-only model, meaning that all of your voice snippets are sent to the cloud for transcription. Despite the similarity in names, Wispr Flow is not based on OpenAI's open-source Whisper speech recognition technology. Wispr Flow appears to be its own model or based on a stack of a variety of model providers. The company does not disclose the exact model used.
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Wispr Flow offers a number of data and privacy options in its settings, including a privacy mode, the option to turn private cloud sync on and off, and local data storage. However, what the options are called in the UI and what the options actually do are different.
Privacy mode isn't really what you would think. It's not that it doesn't look at any of your phrases. It's that when turned on, it will not send any of your data to be used for training the AI.
Private Cloud Sync, when turned off, does not mean that the data is not sent up to the cloud. It means that it's not stored in the cloud to sync to other devices. It is still sent up to the cloud for transcription, but Wispr Flow then deletes the data immediately after transcription.
The local data storage option does not control whether data is stored locally or in the cloud, but instead controls factors like whether or not Wispr Flow will auto-delete local data every 24 hours or never store any data locally, meaning, for example, that the dictation history would not be available to you.
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If you have data control policy concerns, confidentiality concerns, disclosure restrictions, or any other legal reason you don't want your data up in the cloud, you might want to avoid Wispr Flow.
I have found, for basic productivity, that Wispr Flow has become my most actively used voice dictation product. I have been cycling through a bunch of them to try to find one that I could live with as a daily driver. So far, that's Wispr Flow, and that's why it's my top recommendation.
Wispr provided me with a Pro account to use for a year for evaluation, but there's a very good chance that when that year runs out, I will renew it with my own money. That should tell you something. There is a trial version of Wispr Flow that allows you to use it for up to 2,000 words.
Our second tool, Superwhisper , is just chock-full of features. Even so, I just really haven't been able to mesh with it. I am presenting it here because it does have so many specialized capabilities that you may find helpful.
I found the lack of on-the-fly correction to be a deal killer. To be honest, that surprised me because I didn't even realize that I had been using the on-the-fly correction as actively as I was until it became apparent that when it was missing, I missed it greatly.
Superwhisper is available for $8.49 a month, $84.99 a year, or a one-time purchase of $249 that provides unlimited lifetime use. If you think you're going to be using it for a number of years, that's a good deal. On the other hand, AI-based solutions are changing so rapidly that there may be a far better solution, a far cheaper solution, or a free solution available before you fully utilize the unlimited lifetime use. There is a free version that you can use with smaller voice recognition models.
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I should point out that recognition accuracy is not really that much of an issue between the two top products. Both are able to run models that are successful for overall recognition. Although Superwhisper provides a lot of model choices, some of them do not perform voice recognition as accurately but have other advantages.
Superwhisper's biggest advantage over Wispr Flow is that you can create a Mac-only, offline-only, no-data-in-the-cloud version. If you pay for the one-time lifetime use with no additional billing ever, you can own it and control it all and have all your dictation happen entirely on your computer. Superwhisper will do that for you. Wispr Flow will not.
Superwhisper's standout fiddly feature is its mode system . Modes are saved processing pipelines. Basically, what this means is that depending on what mode you're in, Superwhisper can behave or function completely differently.
Beyond processing basic speech, the mode system lets you do some crazy stuff. Take, for example, the idea of dictating a description of a command-line operation that you want to be typed into the terminal, but you describe it like "Give me a directory of my documents." The engine then converts that into an actual command line directly from your dictation.
Another example might be dictating a series of items and having the output be JSON or YAML directly from your dictation.
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Another one might be a devil's advocate mode where you dictate a sentence, paragraph, or concept. Instead of pasting in the dictation, Superwhisper takes that dictation in, processes it, and spits back out an argument against whatever it is that you asserted. This might be useful for students or people researching concepts that they'd like to have dynamically challenged as writing continues. It's powerful. It's very specialized. It might not be usable by everyone, but it is cool.
I never went beyond the free trial for Superwhisper. That's because, despite all of the special features, configuration options, and modes, actual dictation was not as effective as I wanted it to be. When I am looking at an overall voice dictation product, dictation is at the core of my requirements.
If you want to build a dictation system that takes spoken words and turns them into other forms, then Superwhisper is for you. If you simply want to speak and get clean transcription in whatever application you're using, I would not recommend Superwhisper above the other two.
Superwhisper is available for Mac, Windows, and iOS. There is no Android version.
Compared to the other two offerings, FluidVoice is a total bargain. It's free. It's also open source. And it works nearly as well as Wispr Flow in most uses. Almost.
FluidVoice does struggle with on-the-fly correction and dictionary words. For example, FluidVoice has a very hard time with the word ZDNET, even though I've put ZDNET into the dictionary, corrected it multiple times, and done a voice training version of it. It still fails. Whenever I say "ZDNET," I need to retype it by hand.
But even though FluidVoice does struggle, on-the-fly correction does sometimes work fine. Unfortunately, that sometimes happens less than half of the time, but it's better than nothing.
One nice feature of FluidVoice is that it has a little pop-up window that lets you preview the text as you're speaking it. I got used to this when I was using the basic Mac voice processing. It can be helpful to remember what you just said and see how it is being interpreted before you have it pasted into the text you're writing.
FluidVoice has its own native Fluid-1 language processing model, but it also works with OpenAI's Whisper. If you want to use FluidVoice on an Intel Mac, you'll want to connect it to Whisper. If you want to use the Fluid model, which is what I've been testing, you'll need an Apple Silicon Mac. There is no version at this time for Windows or iOS, although the company says versions for both are under development.
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In addition to being free and open source, another key advantage is that you can use FluidVoice entirely offline. That means all of your dictation stays on your machine, and you don't have to worry about how it's being managed.
Of course, if you choose to use one of the cloud models, like OpenAI's Whisper, and run it on a lower-powered Intel Mac, then you will have some cloud processing.
For now, I plan to stay with Wispr Flow because it is the overall most reliable solution for the work I'm doing, especially because of the on-the-fly correction and its dictionary capability. But if I don't feel like spending almost as much as a Netflix subscription for speech recognition, I may move to FluidVoice when it comes time to renew.
If you spend any time at all looking at voice dictation products, you'll run into a whole bunch of contenders. My recommendation is that you choose from the above three. But here's a quick lightning round of additional contenders.
These are systemwide dictation tools you might want to consider.
If you're running MacOS or Windows, these come with the operating system.
Both Anthropic and OpenAI have made recent announcements about their voice input options. They're actually pretty good, but they're limited to use in their own interfaces.
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I've tried voice dictation tools on and off over the years, with limited success. They're still not perfect, but voice dictation has reached the point where it's perfectly usable. Wispr Flow tracks usage stats. I was quite taken aback to realize I had dictated more than 100,000 words since the beginning of February. I knew that Wispr Flow had become a key part of my daily productivity flow, but I didn't know it had become quite that central to my daily work.
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I'm particularly interested in hearing about your experiences with the various tools, so please feel free to share. Would you pay for Wispr Flow's more reliable corrections instead of using FluidVoice for free? Let us know in the comments below.
You can follow my day-to-day project updates on social media. Be sure to subscribe to my weekly update newsletter , and follow me on Twitter/X at @DavidGewirtz , on Facebook at Facebook.com/DavidGewirtz , on Instagram at Instagram.com/DavidGewirtz , on Bluesky at @DavidGewirtz.com , and on YouTube at YouTube.com/DavidGewirtzTV .
