HyperWhisper vs Superwhisper: Which Voice-to-Text App Is Better in 2026?

Superwhisper has built a loyal following as one of the first native voice dictation apps to bring local Whisper models to macOS. Developed by Neil Chudleigh under SuperUltra Inc. and backed by API Capital, it's a solid product with a dedicated community. But when you compare HyperWhisper vs Superwhisper on pricing, model variety, offline capability, and overall value, the differences are significant — and they overwhelmingly favor HyperWhisper.

This comparison of HyperWhisper vs Superwhisper covers every dimension that matters so you can choose the right voice-to-text tool for your workflow.

Privacy: HyperWhisper vs Superwhisper

Privacy is the foundation of any voice dictation app. You're trusting these tools with everything you say — confidential work, personal thoughts, medical notes, legal discussions.

HyperWhisper: Fully Verifiable Privacy

HyperWhisper takes a privacy-first approach that you can independently verify:

• Complete offline pipeline: HyperWhisper includes local Whisper and NVIDIA Parakeet models for transcription, plus Gemma 3 models for post-processing — all running entirely on your device. When using offline mode, zero data leaves your machine. Not even metadata.
• User-controlled cloud: When you opt into cloud transcription, you choose your provider from 12+ options. You know exactly where your audio goes.
• No account required: Download and start transcribing without creating an account or providing personal information.
• Open source backend: HyperWhisper Cloud's backend source code is publicly available on GitHub, so anyone can audit exactly what happens when audio reaches the cloud.
• Verifiable claims: Anyone can confirm audio stays local by monitoring network traffic with tools like Proxyman or Little Snitch.

Superwhisper: On-Device with Cloud AI Formatting

Superwhisper runs whisper.cpp models on-device for base speech-to-text:

• Local transcription: Uses whisper.cpp for on-device speech recognition.
• Cloud for AI formatting: When you use AI-powered modes like Formal, Email, or Message, Superwhisper sends your transcribed text to cloud services like GPT-5, Claude, or Llama for formatting. This means your words still leave your device for the most useful features.
• No open source backend: Unlike HyperWhisper, there's no public source code to audit the cloud processing pipeline.

Both apps take privacy seriously for base transcription. The key difference in the HyperWhisper vs Superwhisper privacy comparison is that HyperWhisper offers a fully offline AI pipeline — transcription and post-processing — while Superwhisper requires cloud connectivity for AI-enhanced formatting.

Pricing: HyperWhisper vs Superwhisper

Cost is where the HyperWhisper vs Superwhisper comparison becomes especially compelling.

Feature	HyperWhisper	Superwhisper
Free tier	3 minutes/day (offline + cloud)	Limited (restricted features)
Paid plan	$39 one-time (lifetime)	$8.49/month or $84.99/year
Lifetime option	$39	$249.99
Subscriptions	None, ever	Required unless you pay $249.99
Offline transcription	Free, forever	Included in paid plans
1-year cost	$39	$84.99–$101.88
3-year cost	$39	$254.97–$305.64

HyperWhisper's one-time $39 payment gives you lifetime access to unlimited transcription, all modes, custom vocabulary, and cloud credits. No recurring charges, no subscription fatigue.

Superwhisper charges $8.49/month or $84.99/year on subscription plans. Their lifetime option is $249.99 — that's 6.4x more expensive than HyperWhisper's lifetime price. Over three years on the annual plan, you'd spend $254.97 with Superwhisper versus $39 total with HyperWhisper.

HyperWhisper's free plan gives you 3 minutes per day of transcription across both offline and cloud modes — enough to try the full experience daily. Superwhisper's free tier is more restrictive, with limited access to features and models.

Features: HyperWhisper vs Superwhisper

Both HyperWhisper and Superwhisper are capable voice dictation tools, but they differ in important ways.

Offline Transcription

Both apps support local transcription with Whisper models, but HyperWhisper goes significantly further.

HyperWhisper ships with a complete offline pipeline:

• 11 Whisper models ranging from Tiny (39 MB) to Large v3 (3.1 GB), including the fast Large v3 Turbo (809 MB)
• NVIDIA Parakeet models optimized for Apple Neural Engine, supporting 25+ European languages
• Gemma 3 models (1B, 4B, or 12B parameters) for fully offline post-processing
• Silero VAD for local voice activity detection

Every step — recording, voice detection, speech-to-text, and AI post-processing — runs fully on-device with zero network calls. This is a true end-to-end offline pipeline.

Superwhisper offers local whisper.cpp models for transcription, but AI formatting modes (Formal, Email, Message, etc.) require cloud connectivity via GPT-5, Claude, or other LLMs. You get local speech-to-text, but not local AI post-processing.

The difference matters. With HyperWhisper, you can dictate a polished email on an airplane. With Superwhisper, you'd get raw transcription only.

Transcription Modes

HyperWhisper provides built-in modes for common workflows: Meeting, Email, Note, Code, Legal, and Medical. Pro users can create unlimited custom modes with specific formatting rules, vocabulary, and writing styles. These modes work with both local and cloud post-processing.

Superwhisper offers built-in modes including Voice, Message, Email, and Formal, plus custom modes. However, AI-enhanced modes require cloud processing.

Custom Vocabulary

HyperWhisper lets you add up to 100 specialized terms, names, acronyms, and jargon per transcription. This works with both local and cloud providers, dramatically improving recognition of domain-specific terminology in fields like law, medicine, and software development.

Superwhisper also offers custom vocabulary support, which is a welcome feature. Both apps recognize the importance of domain-specific accuracy.

Provider Choice

HyperWhisper gives you unprecedented control over your transcription stack:

• 12+ transcription providers: Deepgram, Groq, ElevenLabs, OpenAI, AssemblyAI, Fireworks AI, Mistral, and more
• 30+ transcription models across local and cloud options
• Multiple post-processing providers: Claude, GPT-4, Gemini, Groq, Cerebras
• HyperWhisper Cloud: Built-in edge service deployed across 17 global regions with no API key required

Superwhisper supports BYOK (Bring Your Own Key) for cloud models. However, the selection of integrated providers is narrower, and there's no equivalent to HyperWhisper Cloud's managed edge service that works out of the box without any API key setup.

Language Support

Both apps support 100+ languages through Whisper models. HyperWhisper additionally offers NVIDIA Parakeet models optimized for 25+ European languages with Apple Neural Engine acceleration, providing a second family of local models to choose from.

Platform Support

HyperWhisper is available on macOS and Windows, built with native Swift on Mac and native C++ on Windows. Both platforms get full offline capability and native performance.

Superwhisper supports macOS, iOS, and Windows. However, users report the iOS app's microphone stays active for up to 60 seconds after dictation ends, which raises privacy concerns.

Speed and Accuracy: HyperWhisper vs Superwhisper

HyperWhisper achieves sub-700ms latency with cloud transcription and delivers up to 99% accuracy using state-of-the-art models like Deepgram Nova-3 and ElevenLabs Scribe v2. Custom vocabulary further boosts accuracy for specialized terminology. The post-processing pipeline automatically removes filler words, adds punctuation, and formats output based on your selected mode — whether that's meeting notes, emails, code comments, or medical dictation. Local transcription with Whisper Large v3 or Parakeet models provides excellent accuracy entirely offline.

Superwhisper delivers solid transcription quality through whisper.cpp, and its AI formatting modes produce clean, polished output when connected to cloud models. Users generally report good accuracy, though some note that longer transcriptions can require manual cleanup.

Both apps deliver fast, accurate results for everyday dictation. The advantage in the HyperWhisper vs Superwhisper speed comparison is HyperWhisper's broader model selection — with 30+ models across 12+ providers, you can optimize for speed, accuracy, or cost depending on the task.

Resource Usage: HyperWhisper vs Superwhisper

Both HyperWhisper and Superwhisper are native applications, which is a positive starting point for performance.

HyperWhisper is built with native Swift on macOS and native C++ on Windows. It runs as a lightweight menu bar utility with minimal memory footprint when idle, launching instantly and integrating directly with OS-level APIs for audio capture, hotkeys, and accessibility. Resource usage only scales up during active transcription with local models.

Superwhisper is also a native Swift app on macOS, which means it shares similar baseline performance characteristics. However, local whisper.cpp models can consume significant resources — anywhere from 1GB to 10GB of RAM depending on the model size selected. Some users on Intel Macs report limitations and performance issues with larger models. App crashes have also been reported in user reviews, with an App Store rating around 4.4 stars.

HyperWhisper's advantage here is flexibility. With both Whisper and NVIDIA Parakeet models available, you have more options to balance accuracy against resource consumption. Parakeet models are specifically optimized for Apple Neural Engine, offering efficient performance on Apple Silicon without the heavy RAM demands of the largest Whisper models.

Trust and Transparency: HyperWhisper vs Superwhisper

HyperWhisper:

• Built by an identifiable, public developer (Ray Amjad)
• Open source cloud backend on GitHub
• Privacy claims independently verifiable via network monitoring
• No account required to use the app
• Clear, auditable privacy commitments

Superwhisper:

• Built by Neil Chudleigh under SuperUltra Inc.
• Backed by API Capital
• No open source components for independent auditing
• Cloud AI formatting pipeline remains opaque

Both developers are public and identifiable, which is a positive trust signal. The difference is that HyperWhisper backs its privacy claims with open source code and verifiable offline processing, while Superwhisper's cloud AI formatting pipeline remains opaque.

The Verdict: HyperWhisper vs Superwhisper

When comparing HyperWhisper vs Superwhisper across every dimension, HyperWhisper consistently delivers more for less:

• Better value: $39 once versus $249.99 lifetime (6.4x cheaper) or $84.99/year in subscriptions
• More models: Both Whisper and NVIDIA Parakeet locally, plus 30+ cloud models across 12+ providers, versus whisper.cpp only for local
• True offline AI: Gemma 3 local post-processing for a fully offline pipeline, versus cloud-dependent AI formatting
• More providers: 12+ cloud providers with HyperWhisper Cloud's 17 global edge regions, versus BYOK with fewer integrated options
• More transparency: Open source backend and verifiable privacy versus closed-source cloud processing
• Generous free tier: 3 minutes/day of both offline and cloud transcription at no cost

For anyone who wants more models, a fully offline AI pipeline, broader provider choice, and lifetime access at a fraction of the cost, HyperWhisper is the clear winner in the HyperWhisper vs Superwhisper comparison.

Download HyperWhisper free and experience the difference for yourself.