> ## Content Index
> Fetch the complete content index at: https://www.theaidirectory.com.au/llms.txt
> Use this file to discover other available public pages before exploring further.

# Ollama vs Jan 2026: Which Private Local AI Tool Wins in Australia?
- URL: https://www.theaidirectory.com.au/compare-ollama-vs-jan-australia/
- Published: 2026-06-12T23:00:00.000Z
- Updated: 2026-10-09T06:42:23.000Z
- Description: One is the lean command-line engine the whole local-AI movement runs on. The other is the auditable, no-telemetry desktop app for privacy purists. Here's which Australians should pick.
- Author: Adam
- Tags: Local / Offline & Private AI, #comparison

Head-to-head verdict

[**21**/25Ollama](https://www.theaidirectory.com.au/review-ollama-australia-2026/)[**20**/25Jan](https://www.theaidirectory.com.au/review-jan-australia-2026/)

**No single winner.** The right choice depends on the job; the verdict below says who should buy which.

*Pricing figures updated 6 September 2026: USD prices are converted at the current rate (1 USD ≈ 1.40 AUD, verified 5 September 2026) and shown ex-GST, replacing the retired 1.55 + GST basis. A GST-registered Australian business that supplies its ABN is not charged GST on an imported digital service; other buyers should allow \~10% on top (*[*Methodology*](https://www.theaidirectory.com.au/methodology/)*).*

Both Ollama and Jan solve the same problem: running AI on your own computer so no data ever leaves the building. Both are free. Both are open source. Both keep everything local, which is why each scores a perfect 5/5 on Australian Fit in our reviews. So the choice isn't about privacy — they're level on that. It's about who's sitting at the keyboard.

Ollama is the lean engine the local-AI movement is built on. Jan is the auditable, no-telemetry desktop app for people who need to *prove* their data stays put. Here's how they compare, and which one is right for your Australian business.

## Quick look

|                | Ollama                         | Jan                                       |
| -------------- | ------------------------------ | ----------------------------------------- |
| Our score      | 21/25 — ⭐⭐⭐⭐⭐ Excellent        | 20/25 — ⭐⭐⭐⭐ Very Good                    |
| Australian Fit | 5/5                            | 5/5                                       |
| Best for       | Developers and technical teams | Privacy purists who want an auditable app |
| Interface      | Command line first             | Clean, ChatGPT-style desktop app          |
| Licence        | Open source (MIT)              | Open source (Apache 2.0)                  |
| Price          | Free                           | Free                                      |

Read the full workups: [Ollama review](https://www.theaidirectory.com.au/review-ollama-australia-2026/) and [Jan review](https://www.theaidirectory.com.au/review-jan-australia-2026/).

## What it costs in Australia

This is the easy part: both are free and open source. There's no subscription, no licence fee, no currency conversion and no GST question, because nothing is purchased and nothing is hosted offshore. The only real cost is the computer you run them on — capable models want plenty of RAM and a GPU, and that's true for both.

| Plan                    | Price (AUD, inc. GST)          | Notes                                                            |
| ----------------------- | ------------------------------ | ---------------------------------------------------------------- |
| Ollama (local)          | Free                           | MIT licence; runs on your own hardware                           |
| Jan                     | Free                           | Apache 2.0; analytics off by default, opt-in only                |
| Ollama Cloud (optional) | Pro \~A$31/mo · Max \~A$171/mo | Hosted larger models on Ollama's servers — sends data off-device |

One caveat on that last row. Ollama now offers optional paid cloud tiers (Pro US$20/mo, Max US$100/mo — roughly A$28 and A$140 a month at the current exchange rate, ex-GST). They run bigger models on Ollama's servers, which means your data leaves your machine. That defeats the entire purpose of the category, so for the private, local use case both these tools are about, you simply don't touch it. Jan has no paid tier at all.

## Where they differ

The split is interface and audience, not capability.

**Ollama is command-line first.** You type `ollama run llama3` and it downloads and runs the model. It exposes a local API on your own machine that behaves like a private, in-house version of a cloud AI endpoint, so you can wire it into scripts, internal tools or a chat front-end in minutes. Independent benchmarks put it around 10–15% faster than comparable tools on the same hardware, thanks to lower overhead — a real advantage when you're squeezing models onto finite local resources. It's also the ecosystem backbone: Open WebUI, AnythingLLM and Dify all run on top of it. Even if you never type a command, you may end up running Ollama underneath a friendlier interface.

**Jan is a finished desktop app.** It opens to a chat window, a model picker and a conversation history — much like a cloud AI assistant, except entirely on your machine. There's nothing to wire up and no terminal involved. A non-technical owner can install it and start drafting, summarising or working through ideas straight away.

The privacy posture is where Jan earns its niche. Both tools keep data local, but Jan is fully open source (Apache 2.0) with analytics off by default and opt-in only — and even when switched on, its privacy policy states it never collects your chats, settings, prompts or model choices, only anonymous aggregate metrics via PostHog EU. The code is auditable. For an organisation that needs to *demonstrate* — not just assert — that no data leaves its control, that's a genuine, checkable advantage. Ollama is also open source (MIT) with no telemetry by default, so it's no slouch here either, but Jan makes provable privacy its whole pitch.

The trade-off for Jan is maturity. It's a younger, smaller project than Ollama, so the community, third-party integrations and long-term support are less established. It's actively maintained — v0.8.2 shipped on 1 June 2026 — but Ollama's reach and ecosystem run deeper. Our scores reflect that: Ollama takes Feature Depth 4/5 to Jan's 3/5 and Reliability 4/5 to Jan's 3/5, while Jan edges Ease of Use 4/5 against Ollama's 3/5.

## Which use case picks which

- **You're a developer or run a technical team.** Pick **Ollama**. It's faster, leaner, and it's the engine your other tools will end up running on anyway. Pair it with a front-end like Open WebUI and you get a friendly chat interface on top of its speed — which removes its only real weakness.
- **You're a non-technical owner-operator.** Pick **Jan**. You get a clean, familiar app with no terminal, and the same total privacy. (LM Studio is our Top Pick for general business users, but Jan is the open-source alternative if auditability matters to you.)
- **You must prove data never leaves your control.** Pick **Jan**. Think a law firm's compliance review or a health practice under the Privacy Act. Jan's open-source auditability and analytics-off-by-default posture is the most defensible answer when "trust us" isn't good enough.
- **You want maximum speed and the broadest ecosystem.** Pick **Ollama**. It's the better engine where you have the technical comfort to drive it.

## On Australian Fit — a note

Both tools score 5/5 for Australian Fit, and both clear our Australian Fit gate: a five-star rating, and any category Top Pick, requires Australian Fit of at least 4/5\. They pass for the same structural reason — local execution means no cross-border disclosure under APP 8, no offshore storage and nothing to negotiate on data residency. Neither tool's star rating is capped by the gate. The difference between them is purely the human at the keyboard, not the Australian compliance picture, which is equally strong for both.

## The honest limitation

Neither is built for someone who refuses to install software or read a model name. Ollama assumes you're comfortable in a terminal; Jan, while far friendlier, is still a younger project with a smaller team and ecosystem than the category leaders. If you want the most polished, hand-held experience, our category Top Pick LM Studio is the place to start — but you'll trade Ollama's speed and Jan's open-source auditability to get it.

## The verdict

**For developers and technical Australian teams, Ollama wins** — it's faster, leaner, the ecosystem backbone, and our higher-scored tool at 21/25\. **For privacy purists and non-technical owners, Jan wins** — a clean desktop app with provable, auditable privacy at 20/25\. They're level on what matters most in this category — keeping your data on your hardware — so let the keyboard decide. If you live in a terminal, Ollama. If you want an app you can open and trust, Jan.

## Frequently asked questions

### Which is better for Australians, Ollama or Jan?

The keyboard decides, not the score. Ollama (21/25) wins for developers and technical teams — it's the fast, lean engine most local-AI tools run on. Jan (20/25) wins for privacy purists and non-technical owners who want a clean desktop app with provable, auditable privacy.

### Are they free, and do they bill in AUD?

Both are free and open source, with no subscription, licence fee or currency conversion. Ollama offers optional paid cloud tiers (Pro \~A$31/month, Max \~A$171/month), but those send data off-device — don't touch them for the private use case. Jan has no paid tier at all.

### Do they keep my data in Australia?

Yes — both run entirely on your own hardware, so no data leaves the building. There's no cross-border disclosure under APP 8 and no offshore storage. Both score a perfect 5/5 on Australian Fit; the compliance picture is equally strong for both.

### Which is better if I need to prove my data stays put?

Jan. It's fully open source (Apache 2.0) with analytics off by default and opt-in only, and its policy states it never collects your chats, prompts or model choices. The auditable code is a checkable advantage for a law firm's compliance review or a health practice under the Privacy Act.

## Read next

- [Ollama review (2026)](https://www.theaidirectory.com.au/review-ollama-australia-2026/)
- [Jan review (2026)](https://www.theaidirectory.com.au/review-jan-australia-2026/)
- Category guide: [Best Local & Private AI Tools in Australia 2026](https://www.theaidirectory.com.au/best-local-offline-private-ai-australia-2026/)

## Sources

1. Ollama — https://ollama.com/ — Wayback: https://web.archive.org/web/20260607213226/https://ollama.com/ — checked 13 June 2026
2. Ollama source (MIT, localhost API) — https://github.com/ollama/ollama — Wayback: http://web.archive.org/web/20260606015053/https://github.com/ollama/ollama — checked 13 June 2026
3. Jan — https://jan.ai/ — Wayback: https://web.archive.org/web/20260607213322/https://www.jan.ai/ — checked 13 June 2026
4. Jan Privacy (analytics off by default, opt-in) — https://www.jan.ai/docs/desktop/privacy — Wayback: http://web.archive.org/web/20260601041619/https://www.jan.ai/docs/desktop/privacy — checked 13 June 2026
5. Jan source & releases (Apache 2.0, v0.8.2) — https://github.com/menloresearch/jan — Wayback: http://web.archive.org/web/20251021123628/https://github.com/menloresearch/jan — checked 13 June 2026

**Article structured data (JSON-LD):**

---

*The AI Directory Australia is an independent editorial publication. We don't accept payment for positive reviews. Read our* [*Methodology*](https://www.theaidirectory.com.au/methodology/) *and* [*Affiliate Disclosure*](https://www.theaidirectory.com.au/affiliate-disclosure/)*.*

---