aqua-vs-wispr-flow-v3
Aqua Voice Team
TL;DR: Aqua Voice and Wispr Flow take opposite approaches to voice input. Aqua built its own speech model (Avalon) that gets words right the first time — 97.4% accuracy on technical terms, 31% lower latency, $8/mo. Wispr uses third-party ASR + AI rewriting to polish messy speech into clean text — better for "think out loud" workflows, $15/mo ($12/mo annual). Choose Aqua if you want accuracy. Choose Wispr if you want AI editing. Jump to the switching checklist if you're ready to try both.
You're here because typing is slow and you want to use your voice instead. Maybe you've already tried one of these tools and hit a wall. Maybe you're tired of going back to fix words that should have been right in the first place.
Here's what you need to know: Aqua Voice and Wispr Flow represent two genuinely different philosophies about how voice input should work. Understanding that difference will save you time, money, and frustration.
Quick Verdict
Choose Aqua Voice if you want your words to come out right the first time. Aqua built a proprietary speech model called Avalon that scores 97.4% accuracy on technical terms like kubectl, useState, and LangChain. You speak, it's accurate, you keep moving. $8/mo on annual billing.
Choose Wispr Flow if you prefer to speak freely and let AI transform your thoughts into polished text. Wispr's approach focuses on turning natural, unstructured speech into clean writing. It also has strong team management features and apps on all four platforms (Mac, Windows, iPhone, Android). $15/mo ($12/mo annual).
Aqua Voice | Wispr Flow | |
|---|---|---|
Philosophy | Get it right the first time | Clean it up after |
Monthly price | $10/mo ($8/mo annual) | $15/mo ($12/mo annual) |
Proprietary speech model | Yes (Avalon) | No (uses third-party ASR + Llama for text cleanup) |
Coding term accuracy | 97.4% (AISpeak benchmark) | Not published |
Word Error Rate | 5.52 (best) / 6.24 (public) | Not published |
Streaming real-time mode | Yes | No |
Custom instructions | Yes | No |
Text expansions | Yes | Yes |
API available | Yes (Avalon API) | No |
Latency | 965ms (31% faster) | 1,399ms |
Languages | 49 (6 Avalon-optimized) | 100+ |
Platforms | macOS, Windows (iOS in review) | macOS, Windows, iOS, Android |
Enterprise compliance | Pursuing SOC 2 & HIPAA | SOC 2 Type II, ISO 27001, HIPAA |
Two Philosophies of Voice Input: The Accuracy Tax Framework
We call it the Accuracy Tax: every voice input error costs you 5–15 seconds to fix, and those seconds compound into minutes lost per hour. The question is whether you pay that tax upfront (with a better model) or downstream (with an AI cleanup pass).
Aqua Voice: Accuracy-First
Aqua built its own speech recognition engine, Avalon, from scratch. The entire product is organized around one idea: your words should be correct when they land on screen. No cleanup pass. No AI rewriting what you meant. You said pgvector, and pgvector appears. You said "schedule the Kubernetes deployment," and that's exactly what shows up.
Words stream onto the screen as you speak them, in real time. There's no waiting for a transcription to process. You talk, text appears, you move on.
The bet is simple: if the speech recognition is accurate enough, you don't need a layer of AI editing on top. You just need a really, really good model.
Wispr Flow: Editing-First
Wispr Flow takes the opposite approach. Their homepage literally demonstrates messy, rambling speech being polished into clean prose. The tagline is "Don't type, just speak." The product description says it "turns speech into clear, polished writing."
This approach has real strengths. If you're the kind of person who thinks out loud, who works through ideas by talking before refining, Wispr's pipeline can save a lot of editing time. Wispr has per-app "Styles" that adjust tone depending on whether you're in Slack or a Google Doc. For email, Slack, and document-heavy workflows where polished output matters more than verbatim transcription, this works well.
Wispr has raised $30M+ in funding and acquired Yapify to build their "Voice OS" vision. They have a clear product thesis and a meaningful user base.
The two products solve different problems.
Why This Matters to You
Think about what actually slows you down. Is it typing itself? Or is it going back to fix errors?
If you've ever used voice dictation and spent more time correcting mistakes than you saved by not typing, you've experienced the core problem Aqua solves. When your voice input tool mangles Anthropic into "anthropic" or turns bun into "bun," or renders Deno as "Dino," every correction chips away at the speed advantage.
Wispr's answer: let AI rewrite everything, so errors get smoothed over. Aqua's answer: get the words right so there's nothing to rewrite.
The Model: What's Actually Under the Hood
Aqua Built Avalon
Aqua Voice developed Avalon entirely in-house. It's a proprietary automatic speech recognition model — similar in ambition to what OpenAI did with Whisper but optimized for real-time dictation rather than batch transcription. Avalon is trained, optimized, and deployed on Aqua-managed cloud infrastructure. No third-party model provider sits between your voice and your text.
This means Aqua controls everything: model architecture, training data, inference speed, accuracy improvements, and cost structure. When Avalon improves, only Aqua users benefit.
Aqua publishes its benchmarks. The current public model achieves a 6.24 Word Error Rate (WER), with the latest version reaching 5.52 WER:
Model | WER (lower is better) |
|---|---|
Avalon (latest) | 5.52 |
Avalon (public) | 6.24 |
Deepgram | 6.91 |
Mistral | 6.88 |
Whisper | 7.44 |
Wispr Flow's Architecture
Wispr Flow uses a multi-stage pipeline: a speech recognition engine transcribes your audio, then fine-tuned Llama models hosted on Baseten rewrite and polish the text. This is from Wispr's own co-authored blog post with Baseten, September 2025. According to Crunchbase, Wispr has raised over $30M in funding, most recently a $22M Series A led by NEA in 2024.
This is a valid architecture for the editing-first approach. The ASR layer captures your speech, then the LLM layer transforms it into polished writing. The tradeoff: Wispr depends on third-party infrastructure for both stages.
Wispr does not publish Word Error Rate benchmarks or transcription accuracy numbers, which makes direct numerical comparison difficult. This is consistent with their product philosophy: when the LLM cleanup layer is the core value proposition, raw transcription accuracy is less central to the pitch.
Accuracy: Where the Philosophies Collide
Technical Vocabulary
If you write code, work with AI tools, or use specialized terminology in any field, this is where the accuracy-first approach pulls dramatically ahead.
Aqua created the AISpeak benchmark to measure accuracy on exactly the vocabulary general-purpose models butcher: model names, framework references, programming concepts, terminal commands, API names.
Avalon scored 97.4% on AISpeak. The next-best performer was ElevenLabs at 78.8%.
That gap is the difference between:
"Cursor" and "cursor"
"LangChain" and "lang chain"
"kubectl" and "cube cuddle"
"pgvector" and "PG vector"
"Ollama" and "oh llama"
"useState" and "use state"
Research from Stanford's Human-Computer Interaction lab shows that error correction is the single biggest time sink in voice input workflows. Every one of those corrections takes 5 to 15 seconds. Multiply by dozens of occurrences per day, and you're losing the speed advantage that made voice input appealing in the first place. Wispr's LLM layer can catch some of these errors during rewriting, but it depends on the LLM knowing the correct term. For common frameworks this often works. For newer or niche tools, the correction layer may not have the context to fix what the ASR layer got wrong.
General Accuracy
The accuracy gap extends well beyond technical terms. In Aqua's Human-Scribe benchmark, Avalon achieves 0.9% WER on email dictation, compared to Wispr Flow's 10.5%. For context, human transcription averages about 4% WER. Aqua is literally more accurate than a human transcriptionist on email.
Task | Aqua Voice | Wispr Flow | Apple Dictation |
|---|---|---|---|
0.9% | 10.5% | 17.8% | |
Overall WER (OpenASR) | 5.52 (best) / 6.24 (public) | Not published | N/A |
Lower Word Error Rate means fewer corrections, which means faster overall throughput regardless of what you're talking about.
Some users find they want more control over the output than an editing-first approach provides. A common request across voice input communities is for tools that understand personal context: specific terms, project names, preferred formatting. This is where accuracy-first tools with features like user-defined dictionaries and per-app formatting rules tend to have an edge.
Features That Follow from the Philosophy
Each product's feature set makes sense once you understand the core approach.
Streaming Real-Time Mode (Aqua)
Because Aqua focuses on getting words right the first time, it can show them to you as you speak. Text streams onto the screen in real time. There's no buffer, no delay, no waiting for a block of speech to process. You see your words appear and can course-correct mid-thought.
Wispr Flow doesn't prominently feature real-time streaming. In the editing-first model, showing raw text before the AI cleans it up would undermine the value proposition. You'd see the mess before the polish.
Custom Instructions (Aqua)
Aqua lets you write natural language prompts that control how your speech is transformed: "Always capitalize brand names." "Format code blocks in markdown." "Use British English spelling." "When I say 'new paragraph,' start a new paragraph instead of typing those words."
This is flexible and powerful because it works at the recognition level. You're tuning the model's behavior, not adding a post-processing step.
Wispr Flow offers per-app "Styles" that adjust tone and formatting based on which application you're using. This works within the editing-first framework: different cleanup rules for different contexts. But it's limited to English and desktop only.
Deep Context and Screen Awareness (Aqua)
Aqua's LLM integration references on-screen content to improve accuracy and formatting. If you're looking at a code file and mention a variable name, Aqua uses that context. If you're in a Slack thread and reference the conversation, the correction model understands.
Here's a real example. You say: "Can you modify the canonical title on the context response model to be either an object or a string?" With Deep Context on, Aqua outputs: "Can you modify the canonical_title on the ContextResponse model to be either an object or a string?" It sees your code and formats accordingly.
Context-aware accuracy is a multiplier on Avalon's already-strong baseline.
Text Expansions (Both)
Both Aqua and Wispr Flow support text expansion shortcuts. Speak a trigger phrase and it expands into full text: email signatures, boilerplate code, standard responses. This is not a differentiator. Both do it.
File Tagging for Code Editors (Both, Different Quality)
Both products offer file tagging in editors like Cursor and Windsurf. Wispr Flow mentions file tagging, syntax awareness, and automatic camelCase/snake_case handling. Aqua's implementation goes deeper with context awareness from the code itself.
Whisper Mode (Wispr Only)
Wispr Flow can process whispered speech. If you work in an open office and need to dictate quietly, this is a real advantage. Aqua doesn't currently offer whisper detection.
Speed and Reliability
Speed: WPM and Latency
Aqua users average 179 words per minute, with the top 10% reaching 247 WPM. These are measured averages across the user base. Wispr Flow claims 220 WPM on their marketing site, though the methodology behind that number isn't published.
More importantly, Aqua is 31% faster on latency. The time from when you stop speaking to when text appears: 965ms for Aqua versus 1,399ms for Wispr Flow (tested on clips under 30 seconds, MacBook Pro). Aqua's Instant Mode drops that to roughly 450ms. In Streaming Mode, text appears in real time as you speak.
Metric | Aqua Voice | Wispr Flow |
|---|---|---|
End-of-speech latency | 965ms | 1,399ms |
Instant Mode | ~450ms | N/A |
Streaming Mode | Real-time | Not available |
The real speed question isn't raw WPM. It's: how much time do you spend going back to fix things? If Aqua's output requires fewer corrections, your net throughput is higher even if the raw speaking speed were identical.
Reliability and Infrastructure
Because Wispr Flow's pipeline involves multiple third-party services (ASR + Baseten for LLM rewriting), latency can vary depending on network conditions and service load. Some users have reported occasional slowdowns during high-traffic periods. Wispr's microphone activation speed has been praised, though, so the experience isn't uniformly slow.
Aqua runs Avalon on its own managed cloud infrastructure, giving the team direct control over capacity and latency. Audio processing is private and ephemeral: processed and discarded, never stored or used for training.
Desktop App Quality
Aqua Voice is a native application on both macOS and Windows. If you're running resource-heavy workflows (Cursor, Docker, Chrome with dozens of tabs), a lightweight native app matters. Wispr Flow is also a desktop application, though some users have reported higher memory usage.
The Developer Question
Developers are Aqua's core audience, and it shows. The top five apps used with Aqua are Cursor, VS Code, Claude, Gemini, and iTerm2. If your day involves prompting LLMs, writing code, or working in a terminal, Aqua was built for exactly that workflow.
Why Developers Need Accuracy-First
Developers don't want their voice input to "polish their thoughts." They want their voice input to type what they said. When you're prompting Claude to refactor a function, you need the prompt to be precisely what you intended. An AI rewriting your prompt before it reaches another AI is a game of telephone.
The 97.4% AISpeak accuracy isn't a nice-to-have for developers. It's the entire value proposition. LangGraph, pgvector, Anthropic, bun, Deno, Ollama, FastAPI, Supabase: Avalon handles all of these without manual correction.
The Avalon API
Aqua offers the Avalon API for developers who want to build voice input into their own products. This is a production speech recognition API backed by the same model powering the consumer product.
Wispr Flow has no API. If you want to build on top of voice recognition, Aqua is the only option between these two.
What Developers Say After Switching
"I replaced Wispr Flow with it. I'm a transcription addict. My most common use case is journaling or brainstorming writing but I use it a ton for work as well. I've been using it a lot in Slack and for meetings."
David Rascoe, Ops & Project Manager
"I've tested all the other competitors and Aqua is the only one that works. The custom text prompt for the transcription correction pass is a must-have for me."
Fred Chu, API power user
"Since subscribing, I honestly can't imagine going back to either Dragon or Apple."
Colin, accessibility user
Pricing
Aqua is cheaper at every tier.
Plan | Aqua Voice | Wispr Flow |
|---|---|---|
Monthly | $10/mo | $15/mo |
Annual | $8/mo ($96/yr) | $12/mo ($144/yr) |
Annual savings | $48/yr cheaper | |
Student | ~$3/mo (70% off with .edu) | $6/mo |
Free trial | 1,000-word trial | 14-day Pro trial, then limited Basic |
Team | Available | Available |
Enterprise | Contact sales | Custom (SSO/SAML) |
On annual billing, Aqua costs 33% less than Wispr Flow. That's $48 per user per year. For a 10-person team, $480 in annual savings on top of a proprietary speech model, published accuracy benchmarks, streaming mode, custom instructions, and an API.
The pricing makes sense when you consider the architecture. Wispr pays Baseten for inference. Aqua runs its own model on its own infrastructure. Owning the model means better margins, which means lower prices for the same (or better) quality.
Aqua's student pricing is significantly more aggressive. A 70% discount with a .edu email brings the cost to roughly $3/month, compared to Wispr Flow's $6/month student plan.
Language Support
Aqua supports 49 languages with automatic language detection, including Arabic, Bengali, Cantonese, Mandarin, Hindi, Japanese, Korean, Polish, Portuguese, Thai, Turkish, and more. Six of these (English, Japanese, Spanish, German, French, Russian) get extra accuracy through Avalon-optimized models.
Wispr Flow claims 100+ languages with automatic language detection.
The gap is smaller than it looks. Aqua covers the languages that the vast majority of users actually need. If you work in one of the 49 supported languages, Aqua handles it. If you need Amharic or Lao, Wispr has broader coverage.
Aqua's Japanese support deserves a special mention: the product went viral in Japan organically because voice input is roughly 3x faster than typing in non-Latin languages. Japanese users drove significant adoption without any marketing effort.
Privacy and Compliance
How Your Data Is Handled
Aqua Voice processes audio on Aqua-managed cloud infrastructure. Processing is private and ephemeral: your audio is transcribed and immediately discarded. It is not stored, not used for model training, and not accessible after processing.
Wispr Flow processes audio using Baseten and AWS infrastructure. Wispr has published formal compliance certifications.
Enterprise Compliance
Wispr Flow currently holds SOC 2 Type II, ISO 27001, and HIPAA certifications. These are real, audited commitments that matter for enterprise procurement.
Aqua Voice is currently undergoing SOC 2 and HIPAA audits. If your organization requires these certifications today, Wispr can provide the documentation.
For individual users, freelancers, and startups, both products offer private cloud processing. The compliance question is really about whether your procurement team needs a specific piece of paper before approving the purchase.
Platform Support
Platform | Aqua Voice | Wispr Flow |
|---|---|---|
macOS | Yes | Yes |
Windows | Yes | Yes |
iOS | In App Review | Yes |
Android | No | Yes (launched Feb 2026) |
API | No |
Both Aqua and Wispr now have iPhone apps. Wispr recently launched on Android as well (February 2026), making it the first AI voice input tool available on all four major platforms. Aqua does not currently have an Android app.
The more meaningful platform difference is the API. The Avalon API lets developers integrate production-quality speech recognition into their own applications. Wispr Flow is an end-user product only. If you want voice input as infrastructure, not just an app, Aqua is the only choice.
Developer Tool Integrations
Worth noting: Wispr Flow's voice engine is being integrated into developer tools directly. Codex (OpenAI's coding agent) ships with Wispr Flow for native voice input, and Claude Code launched its own /voice mode in March 2026. Both validate the "voice + coding" workflow that Aqua pioneered. The difference: Aqua works across every app on your system, while these integrations are locked to specific tools. If you use Cursor, VS Code, Slack, email, and a terminal (like most developers do), a system-wide solution still wins.
What Wispr Flow Genuinely Does Better
Honest assessment. These are real advantages:
Team management. Wispr Flow offers shared dictionaries, shared snippets, centralized billing, and usage dashboards for organizations. If you're deploying voice input across a company, these admin features reduce friction.
Whisper mode. Dictating quietly in an open office is a real use case, and Wispr handles it.
Polished marketing and onboarding. Wispr has dedicated landing pages for lawyers, sales teams, creators, students, accessibility, customer support, and more. They've invested heavily in making every persona feel seen. If you want a product that's been packaged for your specific job title, Wispr's website will make you feel at home.
Mobile apps. Wispr launched on Android in February 2026, making it available on all four major platforms. Aqua's iOS app is currently in App Review. If mobile is part of your workflow, Wispr has broader coverage today.
Who Should Choose What
Choose Aqua Voice If:
You're a developer or technical user. The 97.4% accuracy on coding and AI terminology is unmatched. If you spend your day in Cursor, VS Code, Claude, or a terminal, Aqua was built for exactly your vocabulary. See our guide on voice input for Cursor, Claude Code, and AI coding tools for setup tips. Download Aqua and test it on your actual workflow.
You want your words to be right the first time. If your frustration with voice input has always been going back to fix errors, Aqua's accuracy-first approach eliminates that friction. Streaming mode means you see text as you speak, so you're never waiting and wondering what the AI decided you "really meant." Compare this to the best dictation apps of 2026 to see how both stack up against the full market.
You want to spend less. $8/mo versus $12/mo annually ($10 vs $15 monthly). Better accuracy, a proprietary model, real-time streaming, custom instructions, and an API. For less money.
You're building something. The Avalon API is the only production speech recognition API in this comparison. If you want voice input as a building block, not just a tool, Aqua is the only option.
You value transparency. Aqua publishes its accuracy benchmarks. You can verify the claims. Wispr does not publish accuracy data.
Choose Wispr Flow If:
You want AI to rewrite your speech, not just transcribe it. If your workflow is thinking out loud and letting AI turn your rambling into polished emails, reports, or messages, Wispr's editing-first approach is designed for exactly that. Some people genuinely prefer this. It's a different way of working.
You're managing a team deployment. Shared dictionaries, shared snippets, centralized billing, and SSO/SAML make enterprise rollout smoother with Wispr today.
You need mobile support now. Wispr is on all four platforms including Android. Aqua's iOS app is in review and there's no Android app yet.
Your organization requires compliance documentation today. Wispr has SOC 2 Type II, ISO 27001, and HIPAA certifications available now. Aqua is undergoing these audits, but if your procurement team can't wait, Wispr clears the hurdle.
Switching Checklist: How to Test Both Tools in 15 Minutes {#switching-checklist}
Don't trust marketing pages. Test both products on your actual workflow using this checklist:
Step 1: Prepare Your Test Script (2 min)
Copy this test paragraph and read it aloud into both tools. It includes common trip-ups:
Test script (copy this): "I need to refactor the useEffect hook in our Next.js app to call the Anthropic API via LangChain. The pgvector database is running on Supabase, and I want to deploy it using kubectl on our Kubernetes cluster. Can you also check the Ollama integration with llama-cpp and make sure FastAPI handles the WebSocket connection? The PR is in the feat/deno-migration branch."
Step 2: Score the Output (5 min)
For each tool, count:
✅ Correct technical terms (out of 13: useEffect, Next.js, Anthropic, API, LangChain, pgvector, Supabase, kubectl, Kubernetes, Ollama, llama-cpp, FastAPI, WebSocket)
❌ Terms that need manual correction
⏱️ Time from stop-speaking to text-appears (use a stopwatch)
Step 3: Test Your Real Workflow (5 min)
Open your most-used app (Cursor, Slack, VS Code, email) and dictate something you'd actually write today. Note:
Did you have to go back and fix anything?
Did the tool rewrite what you said, or transcribe it verbatim?
Which felt faster end-to-end?
Step 4: Try Custom Instructions (Aqua only, 3 min)
In Aqua Voice settings, paste this starter template:
Common mistake: Setting custom instructions too broadly. Start with 3–5 rules, test them, then expand. Overly complex instructions can conflict with each other.
Results Template
Metric | Aqua Voice | Wispr Flow |
|---|---|---|
Technical terms correct (out of 13) | ___ | ___ |
Latency (seconds) | ___ | ___ |
Manual corrections needed | ___ | ___ |
Overall preference | ___ | ___ |
Save your results.
Switching from Wispr Flow to Aqua
The switch is straightforward. Download Aqua, use the free trial to test it against your real workflow, and compare the results. The accuracy difference is usually apparent within the first few minutes, especially if you use technical vocabulary.
"Aqua Voice took over my life on my computer."
Tim Cakir
"It is a fantastic tool. I started using it this past Saturday, immediately upgraded to the paid version."
Zvi Reiss
Both Aqua and Wispr support text expansion, custom dictionaries, and system-wide input. The features you rely on will transfer. The accuracy will be the thing you notice.
Frequently Asked Questions
Is Aqua Voice better than Wispr Flow?
For accuracy, yes. Aqua's Avalon model scores 97.4% on coding and AI terms and achieves a 5.52 Word Error Rate, the best published score among commercial voice input products. Aqua is also 33% cheaper on annual billing, offers streaming real-time mode, custom instructions, and an API. Wispr Flow has advantages in team management features and currently holds more enterprise compliance certifications.
How much does Wispr Flow cost compared to Aqua Voice?
Aqua Voice costs $10/mo (or $8/mo on annual billing). Wispr Flow costs $15/mo (or $12/mo on annual billing at $144/yr). On annual plans, Aqua saves you $48/year. Both offer student discounts: Aqua at roughly $3/mo with a .edu email, Wispr offers 3 months free + 50% off Pro.
Does Wispr Flow have an API?
No. Wispr Flow is a consumer and enterprise product only. Aqua offers the Avalon API for developers building voice input into their own applications.
Does Aqua Voice work with Cursor and VS Code?
Yes. Cursor and VS Code are the two most-used apps with Aqua Voice. The 97.4% accuracy on coding and AI terminology makes it particularly strong for development workflows, including prompting AI coding assistants.
How many languages does Aqua Voice support?
Aqua supports 49 languages with automatic detection. Avalon-optimized models provide enhanced accuracy for English, Japanese, Spanish, German, French, and Russian. Wispr Flow claims 100+ languages with automatic detection.
Is Aqua Voice good for non-developers?
Yes. While developers are the core audience, Aqua's accuracy-first approach benefits anyone who wants their words transcribed correctly. The top apps used with Aqua include Chrome, Brave, Word, Slack, and LINE alongside developer tools. If you value accuracy over AI rewriting, Aqua works regardless of your profession.
Does Aqua Voice process audio on-device?
No. Aqua processes audio on Aqua-managed cloud infrastructure. Processing is private and ephemeral: your audio is transcribed and immediately discarded. It is not stored or used for model training.
Is Wispr Flow HIPAA compliant?
Yes. Wispr Flow offers HIPAA compliance on all plans, along with SOC 2 Type II and ISO 27001 certifications. Aqua Voice is currently undergoing SOC 2 and HIPAA audits.
Which is better for voice coding and vibe coding?
Aqua Voice. We wrote a full guide on vibe coding with voice input. The 97.4% accuracy on technical terms means your prompts to AI coding assistants come through correctly. Streaming mode lets you see text as you speak, which is essential for iterative prompt engineering. Custom instructions let you control formatting (like always outputting code blocks in markdown). The Avalon API also enables building custom voice-powered development tools.
The Bottom Line
Wispr Flow built a polished editing layer on top of third-party AI models. It's well-funded, well-marketed, and well-suited for people who want to think out loud and let AI handle the writing. It's dictation with a generous AI cleanup pass.
Aqua Voice built the speech recognition itself. A 5-person team — yes, five people — created Avalon, a proprietary model that leads every published accuracy benchmark. It costs less. It streams in real time. It has an API. It gets your words right so you don't need the cleanup.
Different philosophies. The question is simple: do you want a tool that gets it right, or a tool that fixes it after?
Last updated: March 2026. Pricing and features reflect the most current publicly available information for both products. Updated to reflect Wispr Flow's Android launch (Feb 2026), Aqua Voice iOS in App Review, and developer tool integrations (Codex, Claude Code). If anything on this page is inaccurate, contact us at hello@aquavoice.com and we'll correct it.