AI tool comparison
Google AI Edge Gallery vs Stet
Which one should you ship with? Here is the side-by-side panel verdict, pricing read, reviewer split, and community vote comparison.
Mobile AI
Google AI Edge Gallery
Run Gemma 4 and other open models fully on-device — no cloud, no data sent
75%
Panel ship
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Community
Free
Entry
Google AI Edge Gallery is an Android and iOS app that lets users run open-source language models — including the newly released Gemma 4 family — entirely on-device with no internet required. It's essentially a showcase and sandbox for on-device ML, letting developers and power users benchmark models on their own hardware and explore capabilities without any data leaving the device. Version 1.0.11 shipped on April 2, 2026, adding support for Gemma 4 and on-device function calling. The app includes Prompt Lab for parameter testing, AI Chat with visible reasoning traces, image recognition, audio transcription, translation, and a small experimental offline game called Tiny Garden that uses natural language as input. The project has 16.6k stars and is fully open-source. With AICore integration landing in Android, Gemma 4 can run via the OS-level model runtime — meaning future apps can share a single on-device model instance rather than each bundling their own. This is the infrastructure play underneath the gallery.
Productivity
Stet
Local macOS dictation that sounds like you — not like generic AI prose
75%
Panel ship
—
Community
Free
Entry
Stet is an open-source macOS dictation app that transcribes speech locally and then uses AI to clean up the output while actively preserving your personal writing style and tone. The core innovation is a voice model — a lightweight profile that learns from your past writing so the AI corrections don't flatten your voice into generic AI-ese. The result is meant to sound like you dictated it, not like it was passed through a generic LLM. The technical approach combines local Whisper-based transcription (nothing leaves your device during speech-to-text) with an optional AI refinement pass that can use your own API key (BYOK) or a $6.99/month subscription. The open-source release includes the voice profiling code, making it auditable and forkable. It's a direct response to Wispr Flow, which is closed-source and subscription-only. For writers, podcasters, and productivity users who dictate significant amounts of content, the voice preservation angle is genuinely differentiated. The proliferation of AI writing tools has created a recognizable 'AI voice' — flat, over-structured, and devoid of personality — that sophisticated readers are increasingly adept at detecting. Stet's bet is that preserving your actual voice is the most valuable thing an AI writing assistant can do.
Reviewer scorecard
“The function calling demo on-device is the real headline here. If Gemma 4 can handle tool use locally, that's a viable path to offline agents on Android — which opens up use cases in low-connectivity environments that were impossible before. The AICore integration means you write to one API and the OS handles the model.”
“Open-source, local-first transcription with BYOK is the right architecture. I've been burned by voice tools that upload my audio to servers I can't audit. The voice profile approach for preserving style is technically interesting — I want to see how it handles domain-specific jargon and code-switching between formal and casual registers.”
“On-device model performance is still heavily hardware-gated — Gemma 4 running well on a Pixel 9 Pro doesn't mean it runs acceptably on the median Android device. Google controls the showcase, so the benchmarks are cherry-picked for their best hardware. Until AICore reaches broad adoption, this is a preview for early adopters.”
“The 'sounds like you' promise needs a lot of data to actually deliver — your voice profile is only as good as the writing samples it's trained on, and most people don't have a consistent, large corpus of their own writing. For casual dictators, this might just be Whisper with extra steps. Apple's built-in dictation is free and surprisingly good now.”
“The combination of AICore (OS-level model runtime) and on-device function calling is the blueprint for AI that survives network failures, regulatory data-residency requirements, and cloud cost pressures. Google is betting that the edge is where AI matures — this gallery is the proof of concept.”
“Voice-first computing is coming back, and the arms race for authentic AI writing assistance is heating up. The distinguishing factor won't be transcription accuracy — everyone has solved that — it will be voice fidelity. Stet is building in the right direction: local processing plus personal style models. Expect this architecture to be standard in two years.”
“Audio transcription and translation that works offline and doesn't store your recordings anywhere is genuinely appealing for journalists, field researchers, and creators in low-connectivity areas. The privacy story alone makes this worth installing.”
“This is genuinely exciting for writers and content creators. The homogenization of AI-assisted writing is a real aesthetic problem — everything starts sounding like the same LinkedIn post. A tool that actively fights that tendency by learning your specific voice is solving the right problem. Even if the voice model needs work, the direction is exactly right.”
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