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Ekorbia Review 2026: Free Open-Source Local AI Desktop App

Β·10 min readΒ·By Hans Kuepper Β· Founder of PromptQuorum, multi-model AI dispatch tool Β· PromptQuorum

Ekorbia is a free, open-source (MIT-licensed) desktop chat app, built in Rust and Tauri, for running AI models locally on macOS, Windows, or Linux. On macOS it bundles its own inference engine β€” built on llama.cpp β€” with a curated in-app model catalog, so nothing else needs installing. On Windows and Linux it currently requires you to connect an external backend, either Ollama or any OpenAI-compatible endpoint. There is no paid tier, no subscription, no API key requirement for local use, and β€” per its own FAQ β€” no telemetry. It is a very new, very small project: the GitHub repository was created on May 24, 2026, has a handful of releases, and had 1 star at the time of this review.

Ekorbia (ekorbia.com) is a free, open-source desktop chat application, built in Rust and Tauri, for running AI models on your own macOS, Windows, or Linux machine. On macOS it bundles its own inference engine and a curated model catalog; on Windows and Linux it currently connects to Ollama or any OpenAI-compatible endpoint as the model backend. This review is the deep-dive on Ekorbia's entry in the Local LLM Software Directory, covering what the app actually does, its exact pricing (there is none β€” it is entirely free), real download links, and where it fits next to more established local-chat apps.

Ekorbia Review 2026: Free Open-Source Local AI Desktop App

Key Takeaways

  • Ekorbia is free and open-source under the MIT license β€” no subscription, no paid tier, no account, and no API key required for local use
  • On macOS, Ekorbia bundles its own inference engine (built on llama.cpp) plus a curated in-app model catalog (Gemma 4 models and nomic-embed-text for embeddings), so no separate install is needed
  • On Windows and Linux, Ekorbia currently requires an external backend β€” Ollama or any OpenAI-compatible endpoint β€” configured under Settings β†’ Backend
  • Signature features include a Spotlight-style quick-query overlay, folder-based RAG with cited answers, RSS/URL "Watch" monitoring, a markdown-file prompt library, model comparison mode, and private ephemeral chats
  • The project is very small and very new: its GitHub repository was created May 24, 2026, its latest tagged release is v0.7.1 (July 25, 2026), and it had 1 star and 0 forks at the time of this review
  • No founder, team, or company page is published β€” the copyright line reads simply "Β© 2026 Ekorbia," and this review could not verify who built it beyond the GitHub organization name
  • Installers are unsigned on macOS and Windows, so both platforms show a one-time security warning on first launch (documented with a workaround in the project's README)

πŸ“ In One Sentence

Ekorbia is a free, MIT-licensed, Rust/Tauri desktop chat app for local AI on macOS, Windows, and Linux, with a bundled inference engine on macOS and an Ollama/OpenAI-compatible backend requirement on Windows and Linux.

πŸ’¬ In Plain Terms

Instead of paying for a chat app or setting up a separate server, Ekorbia gives you a single downloadable app. On a Mac, it can download and run a model for you directly, no extra software needed. On Windows or Linux, you currently need to install Ollama (or point it at another compatible server) first, then Ekorbia becomes the chat window and workspace on top of that.

πŸ“ŒNote: The Local LLM Software Directory entry for Ekorbia currently lists it as "freemium" and "macOS only." Based on direct verification of ekorbia.com and the GitHub repository for this review, both of those attributes appear to be outdated: Ekorbia has no paid tier at all (fully free) and ships installers for macOS, Windows, and Linux (though several features are macOS-only for now, covered below).

What Is Ekorbia?

**Ekorbia is a native desktop chat and productivity app for running AI models on your own computer, built in Rust and Tauri.** Per its own homepage, it pairs multi-tab local chat with a handful of workspace features not found in a plain chat window: folder attachments answered with citations, background monitoring of RSS feeds and web pages, a global quick-query overlay, and a prompt library stored as plain markdown files on disk.

  • Core function: a desktop chat client that runs AI models locally and stores all conversations, embeddings, and attachments only on your own machine β€” Ekorbia states it has "no analytics, no crash reporter, no accounts, and no servers," per its FAQ
  • On-device inference, technically: on macOS only, Ekorbia bundles its own inference engine (built on llama.cpp) plus an in-app model catalog you download without leaving the app β€” no separate Ollama install is required. On Windows and Linux, per the official FAQ, "that's currently how you supply models": you point Ekorbia at Ollama or any OpenAI-compatible endpoint under Settings β†’ Backend, because Ekorbia does not yet bundle an inference engine for those two platforms
  • Local embeddings: folder-RAG attachments are embedded on-device using nomic-embed-text, per the homepage's technical description
  • Storage: chats, embeddings, prompts, and saved files live in the platform's local application-data directory and a user-chosen prompts folder β€” nothing is uploaded except when downloading a model, polling a Watch URL, or reaching a backend endpoint you configured
  • Developer: no founder, team, or company page is published on ekorbia.com or the GitHub repository at the time of this review; the copyright notice in the project's LICENSE file reads "Copyright (c) 2026 Ekorbia" with no individual name attached

Ekorbia's Project History and Releases

**Ekorbia's public history is short and entirely traceable through its own GitHub releases and blog.** The repository was created on May 24, 2026, and the project has shipped roughly one release every one to three weeks since. No pre-2026 history, founder background, or funding status has been published β€” this review deliberately does not speculate on any of that.

  1. 1
    v0.1.0 β€” May 24, 2026: first release, macOS only, Ollama required
    Why it matters: Per the [v0.1 blog post](https://ekorbia.com/blog), the first release was "a native macOS desktop client for local AI models, running entirely against your own Ollama" β€” the bundled inference engine did not exist yet at this stage.
  2. 2
    v0.2.0 β€” May 26, 2026: chat groups and comparison-chat mode
    Why it matters: This release added sidebar folders for organizing chat history and the side-by-side model-comparison feature (send one prompt to 2–3 models at once, pick the best answer) that is still a headline feature today.
  3. 3
    v0.3.0 β€” June 4, 2026: Windows and Linux support added
    Why it matters: Per the [v0.3 blog post](https://ekorbia.com/blog), this was "the first cross-platform Ekorbia release" β€” native Windows (.msi/.exe) and Linux (.deb/.rpm/.AppImage) builds joined the existing macOS build, at this point still requiring Ollama on every platform.
  4. 4
    v0.4.0–v0.5.0 β€” July 3, 2026: Spaces, offline UI, and voice input
    Why it matters: This pair of releases added an in-app model manager, guided setup, and on-device voice dictation via [whisper.cpp](https://ekorbia.com), per the [official blog](https://ekorbia.com/blog).
  5. 5
    v0.6.0–v0.7.1 β€” July 21–25, 2026: bundled inference engine added
    Why it matters: Per the [v0.6/v0.7 blog post](https://ekorbia.com/blog), this was the release where Ekorbia gained the ability to "run models itself β€” a bundled inference engine with no Ollama and no terminal," alongside a curated model catalog and a Hugging Face model browser with checksum-verified downloads. This bundled-engine capability currently applies to macOS only, per the app's own FAQ.

What Can You Do With Ekorbia?

Ekorbia's feature set centers on turning a single native desktop window into a local-AI workspace, not just a chat box. Here is what each named feature does, per the app's own homepage and documentation.

  • Quick-query overlay β€” a Spotlight-style transparent panel (default hotkey βŒ˜β‡§Space on macOS, Alt+Space on Windows; not yet available on Linux) pops up over any application to answer a question without stealing focus, with its own independent model preference
  • Voice input β€” on-device speech transcription via whisper.cpp, with hands-free auto-stop and auto-send, multilingual coverage across 99 languages, and a translate-to-English toggle; documented as macOS only for now
  • Tabs and full-text search β€” multi-tab chat with independent histories, every reply indexed for BM25-ranked full-text search via SQLite FTS5
  • Private chats β€” an ephemeral session mode (click the lock icon) where nothing is written to the local SQLite database; the conversation exists only in memory and disappears when the tab closes
  • Prompt library β€” prompts stored as individual markdown files with YAML frontmatter in a folder you choose, so they are git-friendly, shareable, and editable in any text editor rather than locked in a proprietary database
  • Compare models β€” send one prompt to 2 or 3 installed models at once, view the replies in side-by-side columns, and click "Keep this" to collapse the losing columns and continue the conversation with the chosen model
  • Screenshot β†’ chat β€” captures a screen region and opens it as a vision-attached chat message, auto-switching to a vision-capable model if the active one cannot see images; documented as macOS only for now
  • Watch (folders, RSS, URLs) β€” polls a folder, RSS feed, or public URL on a set cadence, summarizes only what changed (with a diff-only mode for changelogs), and appends the summary to a notes file, with optional native OS notifications
  • Files and folder RAG β€” attach files or whole directory trees; large files are chunked and embedded locally with nomic-embed-text, and replies return with inline citations linking back to the specific source chunks
  • File generation β€” tool-capable models can call a sandboxed write_file tool to save generated output (code, configs, HTML) to a per-chat output directory, with permission requested on first use and atomic writes to avoid partial-file corruption on a crash
  • Memory file β€” a single markdown file injected as system context on every chat send, read-only from the model's perspective, useful for standing facts you would otherwise retype

Usage Examples: Three Ways to Use Ekorbia

These are concrete workflows built from Ekorbia's own documented features above β€” not hypothetical use cases.

Ekorbia Pricing: Is It Really Free?

Yes β€” Ekorbia has no paid tier of any kind. Per its own FAQ, the app is "free, open-source under the MIT license, with no subscription, no API key, no usage tracking, and no telemetry." There is no /pricing page distinct from the homepage on ekorbia.com β€” the site only has one pricing statement, and it applies to the entire app.

Only tier β€” everything

Price:
$0, no account required
Includes:
Full app: chat, folder RAG, Watch, prompt library, model comparison, private chats, file generation, memory file. Bundled inference engine and model catalog on macOS; Ollama/OpenAI-compatible backend on Windows and Linux.

The only cost to using Ekorbia is whatever hardware and (optionally) Ollama models you already provide yourself β€” the app itself, and every feature it lists, ships with no paywall. This differs from apps like BoltAI, which is a one-time-purchase closed-source app, or Msty, which is free at its core with an optional paid add-on tier β€” verify which pricing model actually fits before assuming any local-chat app follows the same pattern.

Ekorbia vs. Jan: Two Free, Bundled-Engine Apps

**Ekorbia and Jan are the two closest apps in this comparison: both are free, open-source, cross-platform, and bundle their own local inference engine rather than requiring a separate server for every feature.** The clearest difference is maturity β€” Jan has a public license history, a larger contributor base, and years of iteration; Ekorbia is a project a few months old with a single-digit GitHub star count at the time of this review.

Aspect
Ekorbia
Jan
LicenseMITApache 2.0 (with attribution request)
Bundled enginemacOS only (llama.cpp-based)macOS, Windows, Linux (llama.cpp-based)
Windows/Linux local modelsRequires Ollama or OpenAI-compatible endpointBuilt-in, no external backend needed
Project age (this review)Created May 2026; ~4 months oldMulti-year public history
Distinct featuresWatch (RSS/URL monitoring), quick-query overlay, memory fileMCP tool support, local OpenAI-compatible API server
CostFree, no paid tierFree, no paid tier

If you want a bundled local engine that already works the same way on Windows and Linux today, Jan is the more mature choice. If you specifically want the RSS/URL "Watch" monitoring feature or the quick-query overlay, and you are primarily on macOS, Ekorbia's feature set is closer to what you are looking for β€” with the caveat that it is a much newer, much smaller project.

Who Should Use Ekorbia?

Whether Ekorbia fits depends on your platform, whether you are comfortable with an early-stage open-source project, and whether its specific workspace features (Watch, the overlay, the prompt library) matter more to you than maturity and community size.

Ekorbia vs. Other Local Chat Apps

Ekorbia is one of several desktop apps built around local AI chat. Here is how it sits next to other options covered on this site β€” see the Local LLM Software Directory for the full catalog.

  • Jan** β€” a free, open-source, cross-platform app that bundles its own llama.cpp-based engine on macOS, Windows, and Linux alike, with a multi-year public history; the more mature choice if you need a working bundled engine outside macOS today.
  • Msty** β€” a cross-platform (macOS, Windows, Linux) local+cloud chat app with a genuinely free core tier plus an optional paid add-on, and RAG/agent features built in.
  • Enchanted** β€” a free, open-source, native Mac/iOS client built specifically around Ollama, narrower in scope than Ekorbia but with a multi-year track record.
  • BoltAI** β€” a closed-source, one-time-purchase Mac app ($79–$199) that connects to both cloud providers and local models via Ollama/LM Studio, with macOS-specific productivity features layered on top.
  • GPT4All** β€” an open-source local chat client from Nomic AI focused on running models fully offline, with a simpler, longer-established feature set than Ekorbia's Watch/overlay/memory-file bundle.
  • Open WebUI** β€” a self-hosted, browser-based interface typically run alongside Ollama; unlike Ekorbia, it is deployed as a web app rather than a native desktop client.

Common Mistakes When Evaluating Ekorbia

Most confusion about Ekorbia comes from assuming its macOS capabilities apply everywhere, or mistaking its newness for instability.

Frequently Asked Questions

What is Ekorbia?

Ekorbia (ekorbia.com) is a free, open-source (MIT-licensed) desktop chat app, built in Rust and Tauri, for running AI models locally on macOS, Windows, or Linux.

Is Ekorbia free?

Yes, entirely. Per its own FAQ, Ekorbia is "free, open-source under the MIT license, with no subscription, no API key, no usage tracking, and no telemetry." There is no paid tier of any kind.

Does Ekorbia need Ollama?

Only on Windows and Linux, currently. On macOS, Ekorbia bundles its own inference engine and an in-app model catalog, so Ollama is optional. On Windows and Linux, Ekorbia requires Ollama or an OpenAI-compatible endpoint as the model backend, configured under Settings β†’ Backend.

What platforms does Ekorbia support?

macOS, Windows, and Linux, per the official Releases page. Some features β€” voice input and one-keystroke screenshot capture β€” are documented as macOS-only for now, and the quick-query overlay is not yet available on Linux.

Is Ekorbia open source?

Yes. The project is released under the MIT license, with the full source code on GitHub.

How does Ekorbia's on-device engine actually work?

On macOS only, Ekorbia bundles an inference engine built on llama.cpp plus a curated model catalog you download in-app, with no separate install. On Windows and Linux, "that's currently how you supply models" via Ollama or an OpenAI-compatible endpoint instead, per Ekorbia's own FAQ β€” there is no bundled engine on those two platforms yet.

What is the Watch feature in Ekorbia?

Watch polls a folder, RSS feed, or public URL on a set cadence, summarizes only what changed (with an optional diff-only mode for changelogs), and appends the summary to a notes file, with optional native OS notifications.

Who makes Ekorbia?

This review could not find a published founder, team, or company page on ekorbia.com or the GitHub repository. The copyright notice reads "Copyright (c) 2026 Ekorbia" with no individual name attached β€” treat the developer identity as undisclosed rather than assuming a solo founder or a company.

When did Ekorbia launch?

Its GitHub repository was created on May 24, 2026, with the first tagged release (v0.1.0) published the same day. The latest tagged release at the time of this review is v0.7.1 (July 25, 2026).

Is Ekorbia safe to install given it is unsigned?

The installers are unsigned on macOS and Windows because the project does not currently hold a paid Apple Developer or Windows code-signing certificate β€” this triggers a one-time Gatekeeper or SmartScreen warning, not a virus detection. Always download from the official Releases page and verify the published SHA256 checksum before installing, since an unsigned build is easier to impersonate on an unofficial mirror.

Sources

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