# DigUp: Two days after Google released a new model, a Bangladeshi engineer got 6000 GitHub stars · open-source project

> Source: https://stringers.io/en/github/gh_ARahim3__DigUp.html (Stringers / 什么值得做, generated 2026-11-08)
> Stringers answers one question every day: what small product can one or two people build in a few months and actually make money from. Numbers come from 15 databases we collect daily, each with source and date.
> For agents: these verdicts and the underlying databases (verified revenue, App Store / Google Play charts, ad libraries, GitHub, Product Hunt…) are queryable live over MCP — tools today / hot / products / directions / direction / data. Setup: https://github.com/komako-workshop/stringers (the user logs in at stringers.io → "配置 agent" to get a personal URL). Site index: https://stringers.io/llms.txt

> It was the first regular-person-installable app after the new model launched, and the demo explains itself instantly. It debuted on r/LocalLLaMA, Google's official Gemma account reposted it, and a Windows version followed the same day. Those two waves pushed it up.

[GitHub open-source project](https://stringers.io/en/github/index.md) · written 11-6

ARahim3/DigUp · ARahim3

# DigUp: Two days after Google released a new model, a Bangladeshi engineer got 6000 stars

**What it is** A free, open-source desktop search tool. Using Google's newly released EmbeddingGemma 2, it searches your photos, PDFs, recordings, and videos by content on your own computer, and can jump to the exact second in a video.

**Why it caught on** It was the first app an ordinary person could install right after the new model dropped, and the demo makes it obvious at a glance. It launched on r/LocalLLaMA, Google's official Gemma account reposted it, and a Windows version followed the same day, and those two waves pushed it up.

**B** **How you could follow it** Stop building yet another local file search. Watch for the next big company's open-model release, prepare the app shell ahead of time, and ship the first app with a good-looking demo within 48 hours. Launch on r/LocalLLaMA and tag the official accounts.

Grade B: Getting in behind DigUp is no longer open (FileDig, VectorDash, and Rummage all have fewer than 50 stars), and it has dropped into the long tail. The model-launch-day approach can be copied, but it takes community credibility, speed, and a bet on whether the official accounts will repost. It's being talked about in small circles

Data (updated daily) · Repo created 2026-10-08 · 6,306 stars · 7 days +243

GitHub · stars

Data 2026-10-11 → 2026-11-08 (29 days, 29 observations). Points before 10-28 come from deeply / archive backfill, not every day has one

In 2026 Oct 6 Google DeepMind released the multimodal embedding model EmbeddingGemma 2. Two days later, a Bangladeshi AI engineer built a library, and on the third day shipped a Mac app you can install: it searches the photos, PDFs, recordings, and videos on your computer by their content. 29 days later the library had 6260 stars, and the installer had been downloaded about 21k times. The same idea had been open-sourced four months earlier and got only 345 stars. What made the difference, and whether you can pull it off yourself, is what this piece lays out.

### A zebra video

The demo GIF on DigUp's homepage does just one thing: type "zebra in a video" into the search box, press enter, and a video starts playing right from the second the zebra appears. Next, "where they talk about sleep" jumps to the one-minute mark in a podcast, "the clause about pets in the lease" turns to the right page of a rental contract, and "dogs on the beach" is searched in English, Bengali, and Arabic, each returning the same photo.

In Oct 13, Google Gemma's official X account reposted this video, with the first line reading:

> What if Spotlight actually understood the meaning inside your files?

("What if Spotlight could actually understand what's inside your files?"). It was followed by another post, "Credit to @_arahim_". On Oct 27, the official account featured it again in a roundup of community projects built with EmbeddingGemma 2.

### What it is

A free, open-source (MIT) desktop search tool. On Mac it lives in the menu bar and is summoned with ⇧⌘Space; Windows and Linux betas arrived in Oct 14. You pick a few folders, it reads through the images, PDFs, documents, spreadsheets, recordings, and videos inside, and then you describe what you're looking for in plain language, and it finds the matching files, the page, and the moment. Turning on the `code:` toggle also lets you search your own projects by "what does this code do".

Everything runs on your machine: the model is 865 MB, downloaded once, with no account, no uploads, and no data collection. The author wrote the native interface in Swift, with llama.cpp plus Metal underneath, and before installation it tells you how long the first indexing will take.

### Why this one took off

The idea isn't new. Local semantic file search already exists: Fenn is a paid Mac app ($19/mo, $108/yr, lifetime $249); open-source ones like aifs, vgrep, and rememex have 72 to 464 stars; the closest is hanxiao/omni-macos, which open-sourced in Jun 1 2026 years ago: "text, images, audio, and video in one vector space, running locally on Apple silicon." Its author is a co-founder of Jina. It has 345 stars today.

DigUp won on three things.

**Timing.** Model 10-06 launched, the repo was created 10-08, and 10-09 shipped the first installable version, v0.6.0. In the week a new model drops, everyone asks "what can this actually do?" The first solid app regular people can install becomes the answer. Google needed a showcase too, and DigUp was the best-looking one at the time.

**The demo explains itself.** "Jump to the second the zebra appears in the video" needs no explanation of vectors or multimodal models. Press coverage mostly repeated the examples from the README.

**The author had the background and moved fast.** @_ARahim_ previously built mlx-tune (1457 stars), kaggle-tpu-lab, and mlx-dspark, projects that run models on Apple silicon, so he had credibility in the local-model community. He shipped 6 releases in two weeks, and when people asked for a Windows version, he released a beta 10-14.

### Where users come from

Checking against Trendshift's daily numbers (UTC):

| Date | Stars gained that day | What happened that day |
|---|---|---|
| 10-10 | +157 | Author posts a demo video on X |
| 10-11, 10-12 | +793, +910 | r/LocalLLaMA post "Open-source Mac app that runs EmbeddingGemma 2 locally to search your files" (about 1800 upvotes and 241 comments per search snippet, unverified); 10-12 large X account 0xMarioNawfal reposted it |
| 10-13 | +466 | Google's official Gemma account reposted it; the same day's Show HN got only 1 points |
| 10-14 | +1279 | Windows / Linux beta released, covered by Digital Trends (reprinted on Yahoo Tech), and Chinese AI account XiaoHu.AI followed up. Three things stacked on one day. |
| After 10-15 | Over 200 a day, peaking 10-21 to 100, then dropping from 10-28 onward to 20–70 | AI news accounts on Instagram, YouTube, and LinkedIn reposted it; 10-27 Google named it again |

几个值得记下的点:首发在 r/LocalLLaMA,不是 Hacker News——同期 HN 上 EmbeddingGemma 2 本身 439 分,DigUp 的 Show HN 却是 1 分,热度在模型,没流到它身上;Google 官方的那一转,和 Windows 版发布、媒体报道撞在同一天,做出了最高峰;GitHub 官方 trending 不收不满约 60 天的库,它一次都没上过,全靠站外。

### Where it stands now

Over the last 7 days it gained 251 stars, versus 7 stars in the first 524 days. The author hasn't committed since 10-26 (11-06 days as of 11). Windows and Linux are still beta, the installers aren't signed, and Windows shows an "unrecognized app" warning. There are 66 open issues, which means people really are using it.

The copycats have already arrived: r/LocalLLaMA has "FileDig – Windows version of DigUp"; VectorDash (10-10 repo, explicitly "Inspired by DigUp") has 41 stars; Rummage (10-23 repo, Chinese-language, supports Windows and Android) has 27 stars. A knockoff download site, digupguide.com, has even put up a Chinese install tutorial 10-12, forcing the author 10-26 to add "Only download from here" to the README.

These followers show something: **a second DigUp, built after the first, won't get stars.** The first project captured the spot of "first, solid, and shipped in the week a new model drops"; it wasn't the features.

### If it were you

**B.** Don't build a second DigUp, since that spot is gone. The playbook is worth learning: when the next big-company open model launches, ship the first app regular people can install, with a good demo, within 48 hours. The playbook is clear, but each time you're betting on the model and on your speed.

**Who it fits** : developers who already have one or two repos with a thousand-plus stars and some name recognition in r/LocalLLaMA or the local-model crowd on X, and who can build a complete native app (installer, auto-update, first-run onboarding) in two or three days, not just a command-line demo.

**Who it doesn't fit** : anyone wanting to build yet another open-source local file search (FileDig, VectorDash, and Rummage are all under 50 stars), or anyone hoping to make money from it (this category rewards name recognition). Without community credibility, posts go unseen and the launch never gets off the ground.

**How to do it** : keep watching open model releases from Google, Meta, Alibaba, Mistral, and others, and build the app shell in advance (UI, indexing, installer), so that when a model drops you only swap the core. Pick a capability the model makes newly possible that can be explained in one sentence for the demo: a specific second in a video, or cross-language image search. The first screen of the README should be that GIF, not the architecture.

**How to get users** : launch on r/LocalLLaMA and your own X account, with the video in the post. In X posts, tag the model's official account; official developer relations teams need community showcases and will repost them. When people ask for a Windows version, ship it immediately. The second traffic peak came exactly that way. Don't expect HN to help.

**Deadline** : for each model release, the window is only three to five days after launch. DigUp shipped on day three.

**Where this could be wrong** : ① The first community app after the next big model launch may not reach 30 stars within 1000 days. That would mean this time was Google's official endorsement plus one-time luck, not a repeatable playbook. ② Model vendors start shipping official desktop or sample apps themselves, taking the "first" spot. ③ Conversely, if DigUp's author stops updating and Windows stays unsigned, a follower who does a proper Windows version could break past 1000 stars. In that case, the path of "doing the parts DigUp didn't do well" stays open.

### Data and sources

- GitHub: ARahim3/DigUp README and Releases download counts (2026-11-06); daily stars (recorded daily from 10-17 through 11-06).

- Trendshift (trendshift.io/repositories/295333): daily star gains from 10-10 to 10-28; best site-wide daily rank #5 (10-14), Swift daily rank #1 (10-11).

- X: posts from Google Gemma's official account 10-13 and 10-27; post from @RoundtableSpace 10-12.

- Reddit: upvote and comment counts for the r/LocalLLaMA post come from search snippets, unverified; posts for FileDig and VectorDash.

- Hacker News: scores for the Show HN 10-13 and related EmbeddingGemma 2 posts from the same period.

- Press: Digital Trends (10-14), Yahoo Tech, XiaoHu.AI, Gauss Labs News, kocpc.

- Competitors: Fenn pricing from fenn.lemonsqueezy.com; star counts for hanxiao/omni-macos, VectorDash, and Rummage from GitHub.

[GitHub repo ↗](https://github.com/ARahim3/DigUp)

**Research notes: competitor table, acquisition evidence, full research report**

Competitors

| Name | Where | Launched | Scale | How it differs from this one |
|---|---|---|---|---|
| macOS Spotlight / Siri search on macOS 27 | Big-company features | Has always existed; Core Spotlight semantic search since 2024 | All Macs | Mainly relies on file names and text; can't understand the contents of photos, audio, or video, and can't jump to a specific moment. DigUp is marketed precisely as "a Spotlight that understands content." |
| Windows Copilot+ semantic file search | Big-company features | 2025 | Copilot+ PCs only | Requires NPU hardware; DigUp doesn't depend on hardware and runs on ordinary PCs too |
| Fenn | Other | Before and after 2025 (paid Mac app) | Unverified; $19/mo, $108/yr, lifetime $249 | Closest in features (page numbers, timestamps, screen memory), but paid, closed-source, and Mac-only. DigUp is free, open-source, and cross-platform. |
| Dhito | Other | 2026 (paid Mac app) | Not verified | Paid and closed-source, pitched as cheaper than Fenn |
| hanxiao/omni-macos | Open source | 2026-06-01 | 345 star | Almost the same idea, and four months earlier, but it didn't catch the new-model news cycle and had no official endorsement, so it barely grew. |
| openinterpreter/aifs, vgrep, rememex, mango-finder, and others | Open source | 2024–2025 | 72–464 star | Developer tools or plain-text search only; no native app, and no cross-modal or jump-to-moment demo |

Where users come from

- **Verified** **Reddit r/LocalLLaMA / r/LocalLLM launch** : "Open-source Mac app that runs EmbeddingGemma 2 locally…" About 1.8K upvotes and 241 comments per search snippet. 0xMarioNawfal linked this same Reddit post when reposting; corresponds to 10-11 and 10-12 gains of +793 and +910 respectively, 10-12

- **Verified** **Author's own X post + demo video** : @_ARahim_'s original post was quoted by Google Gemma; the author had a base in the MLX/local-model community through projects like mlx-tune

- **Verified** **Google Gemma official X account repost** : 10-13 posted "What if Spotlight actually understood…" and "Credit to @_arahim_"; 10-27 featured it again in a community-projects roundup; 10-14 peaked at +1279

- **Verified** **Tech press and content accounts reposting** : Digital Trends (10-14, reprinted on Yahoo Tech), XiaoHu.AI (10-14), Gauss Labs (10-11), Medium, dev.to, kocpc, an Instagram AI-news reel, and YouTube explainer videos

- **Verified** **Windows/Linux version shipped** : the author posted "You asked, so here it is: DigUp is coming to Windows and Linux"; 10-14 released v0.7.0-beta.1, and that day was the peak

- **Verified** **Hacker News** : the Show HN for 10-13 got only 1 points and 0 comments (hackernews library); it didn't help

## Why DigUp (ARahim3/DigUp) took off

> In short: Google DeepMind released the multimodal embedding model EmbeddingGemma 2 2026-10-06. Two days later (10-08) the author created the repo, and 10-09 he shipped the first installable Mac version, becoming the first ready-made app for "what can this new model do?" A r/LocalLLaMA post and Google Gemma's official X account reposts carried it beyond the niche, and Digital Trends / Yahoo and XiaoHu.AI followed with coverage. It gained 6260 stars in 29 days and about 21k Release downloads. It's free, a personal-brand project from its author.

### 1. Basic data

| items | Numbers | Source |
|---|---|---|
| Repo created | 2026-10-08 20:37 UTC | GitHub API |
| First release v0.6.0 (Mac) | 2026-10-09 | GitHub releases |
| Windows / Linux beta | v0.7.0-beta.1 2026-10-14 | GitHub releases |
| star / fork(11-06) | 6260 / 496 (API time at the moment: 6282) | GitHub repo_day library, GitHub API |
| Total Release asset downloads | About 21,084 (v0.6.1 8382, v0.6.2 4949, v0.7.0-beta.3 2724 …) | GitHub releases API,2026-11-06 |
| Last push | 2026-10-26 (no changes for 11 days) | GitHub API |
| Paid | None. MIT, free, no account, no telemetry | README |

Daily star growth (Trendshift daily table, UTC): 10-10 +157, **10-11 +793,10-12 +910** , 10-13 +466, **10-14 +1279** , 10-15 +485, then ~200 more each day, falling to around 10-21 by 100, and 10-28 onward it's 20–70 a day. Our GitHub repo data (deeply source) records the biggest single day on 10-15 (+1228); that's a one-day offset from the snapshot timing, and it's the same peak as Trendshift's 10-14. Last 7 days +251, the 7 days before that +524: it has entered the long tail.

Trendshift: best overall daily rank #5 (10-14), Swift daily rank #1 (10-11). GitHub's official trending doesn't include repos younger than about 60 days, so it never appeared there (see our repo notes). That doesn't mean it wasn't hot.

### 2. Competitors

| Product | Where | Launched | Scale | How it differs from DigUp |
|---|---|---|---|---|
| macOS Spotlight / Siri search on macOS 27 | Big-company features | Has existed all along. Core Spotlight semantic search since WWDC24; macOS 27 has Siri take over Spotlight | All Macs | Mostly relies on filenames and text. It can't understand what's in a photo and can't jump to a moment in a video or podcast. The macOS 27 redesign also drew complaints (r/MacOS "How is Spotlight file searching in macOS 27", Medium "Siri Replaces Spotlight") |
| Windows Copilot+ semantic search | Big-company features | Rolling out to Insiders since 2025 | Limited to Copilot+ PCs with a 40 TOPS NPU | Needs specific hardware. DigUp runs on ordinary Win10/11, even a 2017-year-old Core i5 (slowly) |
| Fenn(usefenn.com) | Paid Mac app | Around 2025, launched on Product Hunt | Not verified. Pricing $19/month, $108/year, lifetime $249 (fenn.lemonsqueezy.com) | Most similar in features (page numbers in documents, timestamps, screen memory), but paid and closed source. DigUp is free, open source, and cross-platform |
| Dhito | Paid Mac app | 2026 | Not verified | Fenn sells itself as "45% cheaper" compared with others, and it's also paid and closed source |
| hanxiao/omni-macos | Open source | 2026-06-01 | 345 star | Nearly the same idea (text, images, audio, and video in one vector space, running locally on Apple silicon), four months earlier, and the author is a Jina co-founder. But it didn't catch a new-model-launch news cycle, so it barely grew |
| openinterpreter/aifs, CortexLM/vgrep, rememex, mango-finder | Open source | 2024–2025 | 72–464 star | All are developer tools or text-only. None has a native menu-bar app or a "jump to the moment in the video" demo |
| Unsloth Desktop's EmbeddingGemma 2 document retrieval | Open source / other | 2026-10 | Not verified | It's a RAG feature for documents, not whole-disk search of photos and video |

Bottom line: "local semantic file search" was already being built (Fenn charges for it, plus several open-source libraries). **DigUp isn't the first to do this. It's the first complete desktop app to use EmbeddingGemma 2** .

### 3. Where users came from (by time)

1. **The author's own X post + r/LocalLLaMA** : The author (@_ARahim_, an AI engineer from Bangladesh with Apple Silicon / MLX projects like mlx-tune (1457 stars), kaggle-tpu-lab (768), and mlx-dspark (735)) posted an X thread with a demo video. On r/LocalLLaMA, "Open-source Mac app that runs EmbeddingGemma 2 locally to search your files" reportedly got 1.8K upvotes and 241 comments according to a search snippet (Reddit itself wouldn't load, so the numbers come from a Jina search summary and are unverified). It was also posted to r/LocalLLM. 0xMarioNawfal (@RoundtableSpace) 10-12 03:45 UTC relayed it with a Reddit link. These correspond to the +793 and +910 at 10-11 and 10-12. Confirmed.

2. **Batch reposts by media and content accounts (10-11 to 10-14)** : Gauss Labs News (10-11), dev.to, Medium (10-13), **Digital Trends (10-14, syndicated to Yahoo Tech)** , Sinaptica (10-14), **XiaoHu.AI (10-14, a large Chinese AI account)** , kocpc (Taiwan, 10-22), a batch of Instagram AI news reels (Xuan-Son Nguyen, i.e. ngxson of Hugging Face / llama.cpp, posted a demo video that reels quoted), LinkedIn, and YouTube explainer videos. Confirmed.

3. **Amplified by Google's official Gemma X account** : 10-13 16:25 UTC they posted "What if Spotlight actually understood the meaning inside your files?" with a video, quoting the author's original post, then a follow-up "Credit to @_arahim_." 10-27 they also featured DigUp in a roundup of community projects built on EmbeddingGemma 2. Official teams need showcase examples, and DigUp was the most compelling one. Confirmed.

4. **Windows / Linux version (10-14)** : The author posted "You asked, so here it is: DigUp is coming to Windows and Linux." 10-14 they shipped v0.7.0-beta.1, which added +1279 that day, the biggest peak (same day as Gemma's official repost and the Digital Trends article, three things stacked together). Confirmed.

5. **Hacker News didn't help** : The Show HN for 10-13 got only 1 points and 0 comments (hackernews library). Around the same time, EmbeddingGemma 2 itself hit 439 points, and "turning EmbeddingGemma 2 into speech-to-text" got 436 points. The topic's heat was in the model itself, and DigUp didn't catch HN traffic.

6. Product Hunt: nothing found in the library. No sign of paid promotion (it's free and open source, and there's nothing to sell).

### 4. Why it took off

- **Timing** : The model 10-06 launched, 10-08 the repo was created, 10-09 it was downloadable. In the week a new model launches, everyone asks "what can this model actually do?" The first presentable consumer app naturally became the answer.

- **The demo is instantly clear** : "zebra in a video" jumps to the second the zebra appears, "where they talk about sleep" jumps to the minute in a podcast, and searching in Bengali or Arabic finds the same beach photo. These demos turn the model's shared multimodal space into a short clip, which spreads well on X and Reels. Media mostly copied the README examples.

- **Targets a Spotlight pain point** : Everyone has experienced "Spotlight can't find a file I know exists," and macOS 27's search redesign brought another wave of complaints, so Google's official copy was simply "What if Spotlight actually understood…"

- **The author had a track record and shipped fast** : Earlier MLX / Apple Silicon projects with over a thousand stars gave them credibility in the LocalLLaMA community. Native Swift + llama.cpp + Metal, then Windows and Linux added within a week, and 6 releases in two weeks, with a polished result (Homebrew, auto-update, estimating indexing time up front).

- **Free, local, open source** : Products like Fenn charge $108/year. DigUp needs no account and uploads no files. LocalLLaMA users care most about this.

### 5. Differentiation

Versus Fenn / Dhito: free and open source, across three platforms. Versus other open-source libraries: it's a finished native app, not a command-line tool or library for developers. Versus Spotlight / Copilot+: photos, audio, and video all share one semantic space, it can jump to exact timestamps, and it doesn't depend on hardware. Versus the closest match, hanxiao/omni-macos: the idea is nearly identical, and the difference is **it caught the EmbeddingGemma 2 launch and got an official endorsement from Google** . So what actually made it take off was the position of "first, presentable, in the week a new model launched," plus a good-looking demo. Product capability is necessary but not a unique moat.

### 6. How many people know, and whether anyone is copying

- Awareness: **It has spread widely in AI / local-model circles** . Google's official account named it twice, and Digital Trends / Yahoo and XiaoHu.AI covered it. It charges nothing, so there are no public revenue figures.

- Copycats: FileDig (r/LocalLLaMA "FileDig – Windows version of DigUp"), VectorDash (ampersandru, repo created 10-10, 41 stars, post says "Inspired by DigUp," a Windows search alternative), Rummage (CookSleep, repo created 10-23, 27 stars, Chinese-language, supports Windows / Android, nearly the same features), and a dev.to post "Finder Lite." There's also an SEO knock-off download site, digupguide.com (10-12 already hosts a Chinese download tutorial), which forced the author to 10-26 add a "download only from the official source" warning to the README and website. The lattifai/awesome-EmbeddingGemma collection also lists these apps as their own category.

- Current state: star growth has dropped from thousands a day to dozens, and the author hasn't committed in 11 days. Windows / Linux are still beta, and the installers aren't signed.

### 7. What to borrow

- **Watch the release date of big-company open models, and within 48 hours ship the first "consumer-grade, installable app with one good demo," then tag the official accounts.** Official developer-relations teams need community showcases and will repost on their own, which is free distribution from big accounts.

- For the demo, pick examples that were "impossible before and clear in one sentence" (a specific moment in a video, cross-language image search). Don't explain the architecture.

- Launch first in r/LocalLLaMA, where demand is most concentrated, then let media and content accounts repackage it. HN doesn't necessarily buy into this kind of thing.

- When people ask for a Windows version, ship it right away. The second peak came exactly this way.

- On the flip side: projects that rely only on model momentum with no paid tier will lose traffic as the topic fades. If you want to monetize, Fenn's $108/year pricing shows people will pay for this need.

### 8. Still unclear

- Exact upvote count and post time for the r/LocalLLaMA thread (Reddit wouldn't load; the 1.8K / 241 figures come from a search summary).

- Actual retention: how many of the 21k downloads installed and finished a first index. 66 issues suggest real use, but there's no daily-active data.

- Whether the author plans to monetize (the website has no paid option).

- The real scale of paid competitors such as Fenn and how much they've been hit.

### Sources

- [github.com/ARahim3/DigUp](https://github.com/ARahim3/DigUp) (README, releases API, 2026-11-06)

- [trendshift.io/repositories/295333](https://trendshift.io/repositories/295333) (daily star growth, chart ranks)

- Our GitHub library repo_day / repo_profile (2026-10-11 to 11-06); hackernews library story table; producthunt library (no results)

- [x.com/googlegemma/status/2110044337849692644](https://x.com/googlegemma/status/2110044337849692644) (2026-10-13), [x.com/googlegemma/status/2110092927074766867](https://x.com/googlegemma/status/2110092927074766867), [x.com/googlegemma/status/2115150309110743081](https://x.com/googlegemma/status/2115150309110743081) (2026-10-27)

- [x.com/RoundtableSpace/status/2109490491456671940](https://x.com/RoundtableSpace/status/2109490491456671940) (2026-10-12)

- [www.reddit.com/r/LocalLLaMA/comments/1x2eeds/](https://www.reddit.com/r/LocalLLaMA/comments/1x2eeds/) (search snippet), [www.reddit.com/r/LocalLLaMA/comments/1x3djpz/filedig_windows…](https://www.reddit.com/r/LocalLLaMA/comments/1x3djpz/filedig_windows_version_of_digup/), [www.reddit.com/r/LocalLLaMA/comments/1x3sqxc/vectordash_a_fu…](https://www.reddit.com/r/LocalLLaMA/comments/1x3sqxc/vectordash_a_full_windows_search_replacement/)

- [www.digitaltrends.com/computing/digup-ai-natural-language-fi…](https://www.digitaltrends.com/computing/digup-ai-natural-language-file-search-embeddinggemma-2/) (2026-10-14), [tech.yahoo.com/apps/articles/digup-lets-users-mac-files-0011…](https://tech.yahoo.com/apps/articles/digup-lets-users-mac-files-001154403.html)

- [xiaohu.ai/en/article/digup-local-semantic-search/](https://xiaohu.ai/en/article/digup-local-semantic-search/), [news.gausslabs.com/en/arahim3-releases-digup-embeddinggemma-…](https://news.gausslabs.com/en/arahim3-releases-digup-embeddinggemma-search), [digupguide.com/zh/download/mac/](https://digupguide.com/zh/download/mac/)

- [blog.google/innovation-and-ai/technology/developers-tools/em…](https://blog.google/innovation-and-ai/technology/developers-tools/embeddinggemma-2/), [www.marktechpost.com/2026/10/06/google-deepmind-releases-emb…](https://www.marktechpost.com/2026/10/06/google-deepmind-releases-embeddinggemma-2-a-740m-open-multimodal-embedding-model-built-on-gemma-4/)

- [fenn.lemonsqueezy.com/](https://fenn.lemonsqueezy.com/) (Fenn pricing), [dhito.io/compare/fenn/](https://dhito.io/compare/fenn/)

This article was written by AI from public data and the data we collect daily. Numbers are sourced, and inferences are labeled.