The free, private WisprFlow alternative for Mac
Same idea: hold a key, speak, get polished text. The difference is your audio never leaves your Mac, and it costs nothing.
Quick answer
WisprFlow or EnviousWispr: which should you choose?
Choose WisprFlow if you need dictation across Mac, Windows, iPhone, and Android, or want its broader set of snippets, shared dictionaries, app styles, backtrack, meeting, team, and enterprise controls. Choose EnviousWispr if you want free, open-source Mac dictation where audio is always transcribed on your device and no account or subscription is required. WisprFlow is the more mature cross-device service. EnviousWispr is the private, Mac-focused alternative with local speech, optional local polish, direct paste, and Escape Recovery. The key tradeoff is breadth and sync versus local control, price, and source-code transparency. If you move between devices or administer a team, WisprFlow's service model is useful. If you work on one Mac and want fewer external dependencies, EnviousWispr fits that constraint.
Still deciding? See the best Mac dictation apps by use case or browse all 17 dictation app comparisons.
Need to compare several no-subscription choices first? See our free WisprFlow alternatives for Mac.
Feature comparison
An honest look at how the two tools stack up across the dimensions that matter most.
| EnviousWispr | WisprFlow | |
|---|---|---|
| Price | Free. No limits, no subscription. | Free tier (2,000 words/week); Pro $12-15/mo for unlimited* |
| Account required | No | Yes, email signup |
| Audio processing | On-device (Apple Silicon) | Cloud servers |
| Audio leaves your Mac | Never. Audio stays on your Mac. If you enable cloud AI polish, only the text transcript is sent. | Yes, audio uploaded for transcription |
| Offline AI polish | Yes. Transcription + AI polish can both run fully offline via EG-1, Ollama, or Apple Intelligence (macOS 26+). Cloud options (OpenAI, Gemini, Claude) available with your own key. | No. Requires internet for both transcription and AI editing. |
| Speech engines | Parakeet TDT + WhisperKit (on-device) | Cloud speech API |
| Multi-language | 25 European (Parakeet), 99+ languages via WhisperKit | 100+ languages with auto-detection |
| Platforms | macOS only today | Mac, Windows, iPhone, Android |
| Source code | Open source on GitHub (GPLv3) | Closed source |
| Transcription latency | 0.61s median; ~1.65s with on-device AI polish | Depends on network + server load |
| Custom vocabulary | Add names, brands, jargon with fuzzy matching that catches pronunciation variants. | Personal dictionary; auto-learns from corrections. Shared dictionary for teams. |
| Filler word removal | Yes | Yes |
| Writing style control | Voice-preserving AI polish across six engines (EG-1, Ollama on-device; Apple Intelligence on-device, macOS 26+; OpenAI, Gemini, Claude with your own key). | Auto-adjusts tone per app (English, desktop only). |
| Snippets / shortcuts | Not yet | Yes. Voice-triggered text shortcuts with shared snippets for teams. |
| Command mode | Not yet | Yes (Pro only). Edit and rewrite with voice commands. |
| Meeting notetaker | No | Yes, with live transcript, speaker labels, shared notes, imports, and questions over meetings |
| Post-dictation transforms and scratchpad | No dedicated workspace | Yes, reusable Transforms plus a multi-tab rich-text Scratchpad |
| Usage insights | Basic word and time-saved statistics | Detailed: speed, words, corrections, dictionary fixes, app/task breakdown, streaks, and a local Voice Profile |
| MCP and connectors | No | Meeting notes only: MCP excludes ordinary dictations; Google Calendar and Slack connectors support Notetaker workflows |
| First-word capture | Yes, while the mic is warm. A 500ms pre-roll buffer captures audio before recording officially starts; a cold start can still clip. | Not specified |
| Starts listening instantly | Yes. Engine pre-warms on key-down, hiding cold-start and Bluetooth latency. | Not specified |
| Clipboard preservation | Yes, when enabled and no other app changes the clipboard first. | Not specified |
| Text lands in the right app | Yes. Remembers which app and text field were focused, re-activates before pasting. | Not specified |
| AI hallucination safeguards | Yes. Three-layer defense: short-transcript bypass, reinforcement, output validation. | Not specified |
| Hands-free dictation | Yes. Double-press to lock recording. Triple-press to cancel. | Accessibility-focused hands-free support |
| Auto-stop on silence | Yes. Neural voice activity detection stops recording when you finish speaking. | Not specified |
| Accessibility | VoiceOver announcements for recording state changes. | Dedicated accessibility page; hands-free focus for mobility/pain/vision challenges. |
*WisprFlow pricing and features verified from wisprflow.ai/pricing, wisprflow.ai/features, and Wispr Flow 1.6.606 opened directly. Pro is $15/mo billed monthly or $12/mo billed annually. EnviousWispr latency comes from production PostHog data on Apple Silicon Macs. Competitor claims last verified: 2026-08-21.
Why Mac users switch from WisprFlow
EnviousWispr was built to give you everything a premium dictation tool offers, without the tradeoffs.
No subscription, no usage caps, no freemium tiers. Download it, use it, done. WisprFlow costs $15/mo at time of writing, which adds up to $180 per year.
Your audio does not leave your Mac. It is processed by the Neural Engine on Apple Silicon, never uploaded, never stored elsewhere. See how the pipeline works. Private by architecture, not by promise.
Median time to text is 0.61s on Apple Silicon. With AI polish, 1.65s. No network round-trips, no server queues. Immune to bad Wi-Fi.
Download, open, start dictating. EnviousWispr never asks for your email, never requires a login, never phones home. WisprFlow requires account creation before you can use it.
EG-1 and Ollama run entirely on-device, and so does Apple Intelligence on macOS 26+. Want cloud speed? Bring your own OpenAI, Gemini, or Claude key. You control which services touch your text, if any.
Every line is on GitHub under GPLv3. Verify what it does. Report issues directly. Contribute improvements. Closed-source dictation tools ask you to trust their privacy claims on faith.
Where does your voice go?
The most important question for any dictation tool. Here is the data flow for each app. For a deeper dive, read on-device vs cloud dictation privacy.
Fast because there is no upload step
On Apple Silicon Macs, EnviousWispr transcribes speech locally. No network round-trip before text appears.
Based on production data from Apple Silicon Macs. Results vary by hardware and settings.
The details that make dictation reliable
Cloud dictation tools outsource the hard problems to servers. EnviousWispr solves them locally, and the result is a more dependable workflow.
Cloud dictation has a timing problem. While your audio uploads, transcribes, and returns, you might switch apps, click a different field, or start reading something else. When the text finally arrives, it can paste into the wrong place or overwrite your clipboard.
EnviousWispr captures which app and which text field had focus when you started recording. After transcription, it re-activates that exact app and inserts text directly via the Accessibility API. If direct insertion fails, it falls back to an ordinary paste, then to the app's own Edit > Paste menu. If all three fail, your text stays on the clipboard so you can paste it yourself.
The result: text goes where you intended, every time, without trashing what you had copied.
When you run speech through an LLM for cleanup, there is a real risk: the AI can hallucinate extra sentences, "answer" your dictation as if it were a question, or inject preamble like "Certainly! Here is the corrected text." These are not theoretical problems. They happen with basic LLM integrations.
EnviousWispr uses three layers of defense. Short transcripts (three words or fewer) bypass the LLM entirely because there is nothing to polish. Medium transcripts get aggressive prompt reinforcement to prevent creative expansion. All output is validated: if the response is more than three times longer than the input, it is rejected as probable hallucination and the raw transcript is used instead.
The LLM prompt itself is context-aware. It tells the model it is processing speech-to-text output, gives examples of phonetic misrecognition patterns, and adjusts for the app you were dictating into. Your dictated text is wrapped in XML tags with explicit instructions to polish, not answer or execute.
When WisprFlow might be the better choice
WisprFlow is a solid product with a longer track record. It may be a better fit in these situations:
WisprFlow runs on Mac, Windows, iPhone, and Android with settings synced across devices. EnviousWispr is macOS only right now.
WisprFlow has a broader feature set: Notetaker, shared dictionary and snippets, Transforms, Scratchpad, Insights, app-category Styles, voice command editing, backtrack, team tools, and coding-editor awareness. EnviousWispr is catching up, but WisprFlow is ahead on features right now.
WisprFlow offers SOC 2 Type II, ISO 27001, enforced HIPAA compliance, SSO/SAML, and team admin controls. EnviousWispr is built for individual privacy, not enterprise compliance workflows.
If you are Mac-first and care most about privacy, offline transcription, and price, give EnviousWispr a try.
Common questions
Yes. No subscription, no usage limits, no account required. Download and use it. The source code is open source on GitHub under the GPLv3 license.
Transcription runs entirely on-device and works without internet. AI polish requires an LLM; you can use a local model for fully offline operation or bring your own API key for a cloud provider.
No. Your audio is processed on your Mac and discarded after transcription. It never leaves your device, so it cannot be used for anything else.
Yes. Download EnviousWispr, set your keybind, and start dictating. There is no data to migrate. Both apps work in any text field on macOS. See the 2-minute getting started guide.
Any Mac with Apple Silicon (M1 or later) running macOS 14 Sonoma or newer. The Neural Engine on Apple Silicon is what makes on-device transcription fast.
Transcription is always on-device. If you choose to enable AI polish with a cloud provider (OpenAI, Gemini, or Claude), only the text transcript is sent using your own API key. You can also polish with a local model for fully offline operation. The choice is yours.
Yes. EnviousWispr offers on-device transcription on Apple Silicon Macs, completely free, with no account or subscription required. It works offline and keeps your audio on your device.
Open source under the GNU General Public License v3 (GPLv3), an OSI-approved license. You can read, build, inspect, and contribute to every line of code on GitHub. Contributions are welcome.
Rarely. While the microphone is warm, EnviousWispr's pre-roll audio buffer keeps the 500 milliseconds before you press the keybind, so the first word is captured even if you start speaking the instant you press the key. On a cold start there is no earlier audio to draw on, and the first word or two can still be lost.
Nothing, when clipboard restoration is on (the default). EnviousWispr saves your clipboard contents before a clipboard-based paste and restores them afterward, unless another app changes the clipboard in between. Direct text insertion never touches your clipboard at all.
Yes. EnviousWispr has a custom vocabulary system with fuzzy matching that catches pronunciation variants. You can add words with aliases, and on macOS 26+, Apple Intelligence can automatically suggest how the speech engine might mishear your terms. The vocabulary is also fed into the AI polish prompt for double-layer correction.
Ready to try private dictation?
Free to download. No account required. No cloud transcription.