AI-powered voice to text transcription tool for macOS, Windows, and iOS that works in any app with offline and cloud transcription, supporting 100+ languages.
SuperWhisper is an AI-powered voice-to-text transcription tool for macOS, Windows, and iOS that works in any application with both offline and cloud modes, supporting 100+ languages, with pricing starting free and paid plans from $8.49/month. It targets writers, developers, executives, and accessibility-focused users who want to replace typing with dictation across every app on their device.
Built on OpenAI's Whisper models along with proprietary optimizations, SuperWhisper runs locally on Apple Silicon Macs, meaning audio never leaves the device in offline mode â a key differentiator for users handling sensitive information like medical notes, legal drafts, or confidential business communications. The app sits in the menu bar and is triggered by a configurable global hotkey; once activated, users speak and the transcribed text is automatically inserted into whatever field is focused, whether that's Slack, VS Code, Notion, Gmail, or a browser form. Custom modes let users pre-configure different behaviors (e.g., email tone, code formatting, meeting notes) with their own prompts and language models, and SuperWhisper can optionally pipe the transcript through LLMs like GPT-4, Claude, or local models via Ollama for cleanup, translation, or reformatting before insertion.
Based on our analysis of 870+ AI tools, SuperWhisper stands out in the transcription category for its offline-first privacy posture and its "works anywhere" system-level integration, compared to browser-bound tools like Otter.ai or cloud-only services like Rev. While Otter excels at meeting transcription with speaker diarization and Whispr Flow competes directly on the dictation experience, SuperWhisper differentiates on local processing, dictionary customization for jargon and names, and a one-time "forever" license option that's uncommon in this category. The iOS companion app extends the same workflow to iPhone and iPad, with transcripts syncing back to the Mac app via iCloud.
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SuperWhisper runs OpenAI Whisper models locally on Apple Silicon, allowing transcription to happen entirely without an internet connection. This is critical for professionals handling confidential information, since audio and transcripts never leave the device. Users can choose between different model sizes to balance accuracy against CPU and memory usage.
A configurable global hotkey triggers SuperWhisper from anywhere in the operating system, and the transcribed text is inserted directly into whatever app and input field currently has focus. This means it works identically in Slack, VS Code, Notion, Gmail, browser forms, and native apps, rather than being locked to a single editor or extension.
Users can define any number of modes â such as "Email Reply," "Meeting Notes," or "Code Comment" â each with its own LLM, prompt template, and language settings. Switching modes reshapes how the transcription is processed, enabling the same voice input to produce polished email copy in one mode and structured bullet notes in another. This turns SuperWhisper into a programmable voice interface rather than a static dictation tool.
Beyond raw transcription, SuperWhisper can pipe text through GPT-4, Claude, Gemini, or local models via Ollama to clean up grammar, translate, summarize, or reformat before insertion. Users bring their own API keys, keeping data flow under their control. This bridges the gap between raw speech and polished, context-appropriate written output.
SuperWhisper lets users add custom words, names, acronyms, and domain jargon that standard Whisper models frequently mistranscribe. Medical terms, product names, teammate names, and technical acronyms can all be enforced, dramatically improving accuracy for specialized workflows. This is particularly valuable for engineering, medical, and legal users whose vocabularies differ from general training data.
$0
$8.49/month (billed annually)
One-time purchase
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SuperWhisper continues to expand its Windows client toward feature parity with macOS, adds newer local models and expanded LLM provider support (including Claude and local Ollama models), and has rolled out deeper custom-mode workflows and voice-triggered actions for automating tasks beyond plain transcription.
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