Gallery Alternatives

gallery reviews and mentions

• Gemma 4 on Android: Tricks for Faster On-Device Inference
  1 project | dev.to | 23 May 2026

  For document Q&A specifically, this is worth implementing. The user loads a document, the prefill runs once and the state is serialized to disk. Every subsequent question in that session resumes from the cached state rather than reprocessing the document from scratch. The Google AI Edge Gallery app is the most complete open-source example of session management in a real LiteRT-LM application.

• Google Gemma 4 Runs Natively on iPhone with Full Offline AI Inference
  2 projects | news.ycombinator.com | 15 Apr 2026

  They released the source (well, currently only the Android version) at https://github.com/google-ai-edge/gallery .

  At a glance, I see they do gather analytics about how much the app is used (model downloads, model invocations etc) without the actual message content.

• From Intent Classification to Open-Ended Action Spaces: Why Mobile Testing Needed a New Paradigm
  1 project | dev.to | 5 Apr 2026

  Google recently shipped AI Edge Gallery — an on-device AI sandbox app with a feature called "Mobile Actions" that lets you control your phone with natural language. Say "turn on the flashlight," and a 270M parameter model called FunctionGemma figures out the intent, extracts the parameters, and dispatches the right function call. It runs entirely offline. It clocks 1,916 tokens/sec prefill on a Pixel 7 Pro. And it's impressive.

• Gemma 4 on iPhone
  7 projects | news.ycombinator.com | 5 Apr 2026

  Two (very quick) minutes on their GitHub repo and it's pretty obvious that they're using firebase-analytics and at the very least seem to be sending URLs[1] and infos such as the model you download or the capacities[2] you use.

  1. https://github.com/google-ai-edge/gallery/blob/main/Android/...

• Google releases Gemma 4 open models
  10 projects | news.ycombinator.com | 2 Apr 2026

  Google AI Edge Gallery: https://github.com/google-ai-edge/gallery/releases

• Show HN: Off Grid – Run AI text, image gen, vision offline on your phone
  4 projects | news.ycombinator.com | 14 Feb 2026

  Looks useful, though something went wrong doing NPU image generation on my phone.

  Reminds me a lot of https://github.com/google-ai-edge/gallery which is a proof-of-concept app by Google themselves for their AI libraries. However, your app supports more and larger models without having to manually import anything, which is very useful.

• Smarter Notifications with Edge AI: A Kotlin + Koog + MediaPipes Journey
  4 projects | dev.to | 2 Oct 2025

  Google Edge AI Gallery app repository

• Qwen3 30B A3B Hits 13 token/s on 4xRaspberry Pi 5
  4 projects | news.ycombinator.com | 6 Sep 2025

  1. This is Q4

  2. This remain slow

  3. The context window used here is likely 8k or similar which makes it unusable for bigger input/output.

  Models already work fine on phones just try https://github.com/google-ai-edge/gallery and you will see local AI running on phones fine.

• OpenAI Open Models
  15 projects | news.ycombinator.com | 5 Aug 2025

  Have you tried Google's Gemma-3n-E4B-IT in their AI Edge Gallery app? It's the first model that's really blown me away with its power-to-speed ratio on a mobile device.

  See: https://github.com/google-ai-edge/gallery/releases/tag/1.0.3

• Gemma 3n: The Developer Guide
  6 projects | news.ycombinator.com | 26 Jun 2025

  Somethings really screwy with on-device models from Google, I can't put my finger on what, and I think being ex-Google is screwing with my ability to evaluate.

  For instance:

  "High throughput: Processes up to 60 frames per second on a Google Pixel, enabling real-time, on-device video analysis and interactive experiences."

  You can download an APK from the official Google project for this, linked from the blogpost: https://github.com/google-ai-edge/gallery?tab=readme-ov-file...

  If I download it, run it on Pixel Fold, actual 2B model which is half the size of the ones the 60 fps claim is made for, it takes 6.2-7.5 seconds to begin responding (3 samples, 3 diff photos). Generation speed is shown at 4-5 tokens per second, matching what llama.cpp does on my phone.

  So, naively, we're looking at a 0.16 frames a second, not 60 fps.

  I used to work on Pixel, and I remember thinking that it seemed like there weren't actually public APIs for the TPU. Is that what's going on?

  In any case, this is the 3rd or 4th Google on-device release the last couple years where it wasn't anything special w/r/t on-device performance.

  The blog post is so jammed up with so many claims re: this is special for on-device and performance that just...seemingly aren't true. At all.

  - Are they missing a demo APK?

  - Was there some massive TPU leap since the Pixel Fold release?

  - Is there a lot of BS in there that they're pretty sure won't be called out in a systematic way, given the amount of effort it takes to get this inferencing?

  - Is this supposed to run on some Pixel-TPU-private-API?

• A note from our sponsor - SaaSHub
  www.saashub.com | 15 Jun 2026

  SaaSHub helps you find the best software and product alternatives Learn more →