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Comparison

Conduit vs Ollama's own app

We make one of these, so read it the way you would read any vendor comparison. This one is unusual, though: these are not really rivals. Ollama is the engine, Conduit is a window onto it, and the honest answer for most people is that they run both. Ollama details below were checked against Ollama's own blog, documentation, and issue tracker on 12 September 2026 — if something has changed since, their sources are right and this page is wrong.

The short answer

Use Ollama's own app if you want to chat with local models and nothing more. It is already installed, it manages your models, and it is made by the people who make the engine. For "I pulled a model, now let me talk to it", nothing here beats it, and adding a second application would be pure overhead.

Add Conduit on top when the client itself starts mattering: MCP tools, hosted providers side by side with local ones, conversations you can search months later, artifacts, or shipping the client under your own brand. Conduit does not replace Ollama and cannot run a model without it — it replaces the chat window.

Side by side

 Ollama's appConduit
What it is The engine, with a chat interface built in A client. Needs Ollama, or another provider, behind it
Runs model weights Yes — this is the product No — it calls Ollama's API
Pull, delete, upgrade models Yes, from the app No. It lists what you already have and chats with it
Platforms The app is macOS and Windows; command-line builds cover Linux Windows, macOS, Linux (.deb and AppImage), no feature differences
MCP tools An open feature request (issue 7865, filed November 2024) Yes — local stdio and remote streamable HTTP with OAuth
Other providers Ollama models, local or its hosted cloud ones 17 built in, Ollama among them — local and hosted side by side, hosted ones using your own keys
Files and images Drag in text and PDFs; images to multimodal models Attachments and images, content-addressed on disk. Documents collections add persistent, searchable retrieval over text, Markdown, CSV, Word, and PDF files, rather than pasting a whole file into context
Conversation history In the app SQLite on your disk, with full-text search across everything
Artifacts No Code, JSON, Markdown, Mermaid, KaTeX, sandboxed HTML, exportable
Code-signed installers Yes No — SmartScreen and Gatekeeper warn on first launch
Rebrandable No Runtime branding today; packaging is early access from source

Where Ollama's own app is better

It manages the models, and we don't. Conduit calls exactly two Ollama endpoints: one to list what you have, one to stream a conversation. Pulling a new model, deleting an old one, upgrading — all of that stays in Ollama. If you try models constantly, the built-in app is the better daily driver and it is not close.

It is one install, by one team. The engine and the interface ship together and are versioned together. Nothing to configure, no base URL to get wrong, no second app to keep updated, and when something breaks there is one project to report it to.

It installs without a warning. Ollama's binaries are signed. Conduit's are not yet, so a first launch puts a SmartScreen or Gatekeeper warning in front of you. If you are setting someone else up, that warning is a real cost.

Where a separate client adds something

Tools, via MCP. Ollama is a model server; giving a local model access to your files, a database, or an API means something else has to speak the Model Context Protocol and call Ollama for inference. Conduit does that directly — local servers as supervised child processes with consent prompts per tool, remote ones over streamable HTTP with OAuth. This is the single biggest functional gap between the two.

Local and hosted models in one window. A small local model handles the bulk cheaply; a frontier model handles the hard question. 17 providers ship built in — Ollama and LM Studio locally, hosted ones with your own keys — so switching between them is a dropdown in the same conversation list rather than a different application.

Retrieval over your own files. Documents collections index text, Markdown, CSV, Word, and PDF files with hybrid vector and keyword search, and a reply names the passage it drew on. With Ollama as the embedding provider — or local-only mode, which requires it — indexing stays on the machine too. Ask for a picture and, on OpenAI, Gemini, or OpenRouter, Conduit generates and saves one locally.

Conversations you can still find later. Everything lands in a SQLite database on your disk with full-text search across every conversation, reachable from the command palette. No account, and nothing proxied through a server we run.

Genuinely offline, when you want it. Local-only mode stops the app making outbound requests at all. Paired with Ollama that is a complete assistant with no network — the shape that air-gapped and some regulated environments require.

One thing worth knowing about "local"

Ollama is no longer only local. Alongside models on your own hardware it now offers hosted cloud models, offloaded to Ollama's own service and reached with an account created through ollama signin or an API key. Local-only use remains entirely possible and is what most people do — but if you chose Ollama specifically because nothing left the machine, that is now a setting rather than a property of the tool. The same caution applies to us: Conduit is local-first by construction, and local-only mode is the switch that makes it absolute.

What Conduit does not do

Which should you use?

Start with Ollama's app, because you already have it. If you find yourself wanting a model to actually do something — read a file, call an API, run a tool — or wanting one window over both a local model and a hosted one, add a client. That is the point at which a separate application earns its place, and not really before.

Download Conduit

Comparing more broadly? Best MCP clients, compared covers the desktop, self-hosted, and IDE-shaped clients side by side. Weighing a local model against a paid key on cost, the break-even page does the arithmetic.

More comparisons: all Conduit comparisons, including Conduit vs LM Studio, Conduit vs Msty, and Conduit vs Open WebUI.

Questions

Does Ollama have a GUI?

Yes. Ollama ships an official desktop app on macOS and Windows that downloads and chats with models, accepts dragged-in text and PDF files, sends images to multimodal models, and exposes context length in its settings. It is a real app, not a wrapper someone else made. Standalone command-line builds remain available from Ollama's GitHub releases for anyone who wants only the engine.

Do I still need Ollama if I use Conduit?

Yes, for local models. Conduit does not run model weights — it connects to Ollama over its HTTP API and lists whatever you have pulled. Ollama stays installed and stays the thing doing inference. Conduit replaces the chat window, not the engine, which is also why the two coexist without conflicting.

Can I use MCP tools with Ollama?

Not from Ollama itself today. Built-in Model Context Protocol support is an open feature request on Ollama's tracker — issue 7865, filed in November 2024 and still open. The usual route is a client that speaks MCP and calls Ollama for inference, which is the arrangement Conduit provides: the protocol work happens in the client, the tokens come from Ollama.

Is Ollama entirely local?

Not by default any more. Alongside local inference, Ollama now offers hosted cloud models that are offloaded to its own service, which needs an account through ollama signin or an API key. Local-only use is still entirely possible — it is what most people do — but "I use Ollama" no longer implies on its own that nothing left the machine. Worth knowing if that distinction is the reason you chose it.

Can I pull and delete models from Conduit?

No. Conduit reads the list of models you already have and streams chat against them — those are the only two Ollama endpoints it calls. Pulling, deleting, and upgrading models stays in Ollama, whether through its own app or ollama pull on the command line. That is a genuine point in the built-in app's favour if you switch models often.

Sources for the Ollama rows, checked 12 September 2026: Ollama's announcement of its app, its cloud documentation, and issue 7865 for MCP support, which was open on that date. Conduit rows are checkable against the documentation and the source. Found an error? Tell us and we will fix it.

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