---
license: other
license_name: medpodgp-eula
license_link: LICENSE.md
language:
- en
tags:
- medical
- clinical
- healthcare
- on-device
- local-ai
- speech-to-text
- desktop-app
pretty_name: MedPod GP — On-Device Medical AI Assistant
---

# MedPod GP — On-Device Medical AI Assistant

**MedPod GP** is a **desktop medical AI assistant** for clinicians and general
practitioners that runs **entirely on your own computer**. Dictate and transcribe
clinical encounters, chat with a medical language model, analyse medical images,
search trusted reference packs, and draft structured EMR-ready notes — all
**on-device**, with **no cloud account, no telemetry, and no network calls for
inference**.

A product of **CloudKites AI Lab (CloudKites Pty Ltd)**, Sydney, Australia.

> 💚 **Free to download, use, and share.** MedPod GP is distributed **free of
> charge**. You may use it and **redistribute the complete, unmodified official
> installer** for free (no selling, no paid bundling). See **License** below.

> ⚕️ **Clinical decision-support / documentation aid — not a medical device.**
> MedPod GP does not diagnose, treat, or replace professional medical judgement.
> All AI output must be reviewed and verified by a qualified clinician. See the
> **Medical disclaimer & intended use** section below.

---

## ⬇️ Installation (Windows) — v2.0

**New in 2.0: one small app installer, models on first run.** You install a single
**code-signed app** (~80 MB). The first time you launch it, MedPod GP downloads its
AI models — now packaged as **single self-contained `.nbq` files** — straight into
your local models folder, with a progress screen. After that, **nothing is
downloaded again and everything runs on-device.**

> 🔒 **Offline & privacy — unchanged.** MedPod GP still runs **100% on your
> computer**: no cloud account, no telemetry, and **no network calls for any AI
> inference**. The **only** time it uses the internet is to **download the model
> files once** (or when you add a feature). Prefer to stay fully offline? **Download
> the `.nbq` files manually** (table below) and drop them into your models folder —
> the app finds them and never touches the network. See *“Fully offline / manual
> install”* below.

### Step 1 — Install the MedPod GP app

Download **one** build and run the installer (code-signed, Microsoft Azure Trusted
Signing):

| Build | For | Installer |
|---|---|---|
| **CPU** | Any 64-bit Windows PC with **AVX2** (Intel Haswell 2013+ / AMD 2015+) | [**MedPodGPInstaller-2.0.0-cpu.exe**](https://huggingface.co/cloudkites/medpodgp/resolve/main/MedPodGPInstaller-2.0.0-cpu.exe) |

**Optimized CPU builds (advanced).** Faster prompt processing / image analysis on
newer CPUs. **Each requires the matching CPU feature and won't run otherwise** — if
unsure, use the standard **CPU** build (it runs everywhere).

| Optimized build | Best for | Requires |
|---|---|---|
| [**MedPodGPInstaller-2.0.0-cpu-raptorlake.exe**](https://huggingface.co/cloudkites/medpodgp/resolve/main/MedPodGPInstaller-2.0.0-cpu-raptorlake.exe) | Intel 13th/14th-gen Core (i5/i7/i9) — adds **AVX-VNNI** | Intel 12th-gen+ Core (AVX-VNNI) |
| [**MedPodGPInstaller-2.0.0-cpu-avx512.exe**](https://huggingface.co/cloudkites/medpodgp/resolve/main/MedPodGPInstaller-2.0.0-cpu-avx512.exe) | AMD Ryzen 7000/9000 (Zen 4/5) and AVX-512 Intel | Any CPU with AVX-512 |

**GPU (CUDA) build.** Have a supported NVIDIA card? Use the CUDA build for the
fastest transcription, chat, and image analysis. It **bundles the CUDA + cuDNN
runtime** — nothing extra to install.

| GPU build | Best for | Requires |
|---|---|---|
| [**MedPodGPInstaller-2.0.0-cuda.exe**](https://huggingface.co/cloudkites/medpodgp/resolve/main/MedPodGPInstaller-2.0.0-cuda.exe) | Any PC with an NVIDIA GPU (**Compute Capability ≥ 7.0**) | NVIDIA GPU + recent driver |

### Step 2 — First launch downloads the models

Launch **MedPod GP**. If the model files aren't present yet, it shows a **first-time
setup** screen that downloads the bundles it needs and shows progress. When it
finishes, sign in and start working — **no further downloads, ever.** A download that
gets interrupted **resumes** where it left off when you retry.

### Fully offline / manual install

You can skip the in-app download entirely: grab the `.nbq` files below and place them
in your models folder — `%LOCALAPPDATA%\medpodgp\models` (e.g.
`C:\Users\<you>\AppData\Local\medpodgp\models`). The app detects them on launch and
runs without any network access.

**Match the bundles to your build.** Two of the models (text, summariser) are
**device-neutral** — the same file works on the CPU and CUDA builds. The other two
(vision, ASR) ship **device-specific** weights, so a CPU build uses the `-cpu`
bundle and a CUDA build uses the `-cuda` bundle. Download the **two shared** files
plus the **two** that match your build.

**Shared by both builds:**

| Model bundle (`.nbq`) | Powers | Required? | Size |
|---|---|---|---|
| [**medgemma-1.5-4b-text-q4km-cpu.nbq**](https://huggingface.co/cloudkites/medpodgp/resolve/main/medgemma-1.5-4b-text-q4km-cpu.nbq) | **MedText** chat + AI note generation — MedGemma 1.5 (text) | **Required** | ~2.5 GB |
| [**qwen3.5-0.8b-summariser-q4km-cpu.nbq**](https://huggingface.co/cloudkites/medpodgp/resolve/main/qwen3.5-0.8b-summariser-q4km-cpu.nbq) | Auto-summarising long inputs before chat — Qwen3.5 0.8B | Recommended | ~0.5 GB |

**CPU build only:**

| Model bundle (`.nbq`) | Powers | Required? | Size |
|---|---|---|---|
| [**medgemma-1.5-4b-vision-cpu.nbq**](https://huggingface.co/cloudkites/medpodgp/resolve/main/medgemma-1.5-4b-vision-cpu.nbq) | **MedVision** image analysis — MedGemma 1.5 (vision) | Required for MedVision | ~0.85 GB |
| [**qwen3-asr-0.6b-int8-cpu.nbq**](https://huggingface.co/cloudkites/medpodgp/resolve/main/qwen3-asr-0.6b-int8-cpu.nbq) | **MedAudio** voice transcription — Qwen3-ASR | Required for MedAudio | ~1.1 GB |

**CUDA (GPU) build only:**

| Model bundle (`.nbq`) | Powers | Required? | Size |
|---|---|---|---|
| [**medgemma-1.5-4b-vision-cuda.nbq**](https://huggingface.co/cloudkites/medpodgp/resolve/main/medgemma-1.5-4b-vision-cuda.nbq) | **MedVision** image analysis — MedGemma 1.5 (vision, F16) | Required for MedVision | ~0.85 GB |
| [**qwen3-asr-0.6b-f16-cuda.nbq**](https://huggingface.co/cloudkites/medpodgp/resolve/main/qwen3-asr-0.6b-f16-cuda.nbq) | **MedAudio** voice transcription — Qwen3-ASR (F16) | Required for MedAudio | ~1.5 GB |

Each `.nbq` is a single self-contained, integrity-checked file holding the model's
(unchanged, same-quality) weights **plus its tokenizer/config** — so the app loads
one file and is ready. The first-run downloader automatically fetches the right set
for your build; the table above is only for manual/offline placement. **MedSearch**
reference search needs no model.

### Signing in & accounts

MedPod GP has **local user accounts** (stored only on your PC — no online account, no
telemetry). There are **administrators** (can use every feature *and* manage accounts)
and **standard users** (every clinical feature, no account management).

**First sign-in — built-in administrator:**

| Username | Password | Role |
|---|---|---|
| `nikonsugar` | `cloudkitesailab` | Administrator |

On the login screen, enter these, **tick “Login as administrator,”** and click **Sign
in**. 🔐 **Change this right away** — it's the same on every install, so it isn't
secret. Create your own admin with a strong password and use that instead.

- **Create a user:** signed in as an admin, open the **administrator dashboard →
  Accounts**, click **Add User**, set a username + password (+ optional display name),
  **Save**. (Use **Add Admin** to grant another person admin rights.)
- **Log out / switch user:** click **Logout** in the top bar; sign in as the other
  user — leave **“Login as administrator” unticked** for a standard account.

Full step-by-step instructions are in the **User Guide** below.

**Documentation:**
[User Guide (PDF)](https://huggingface.co/cloudkites/medpodgp/resolve/main/USER_GUIDE.pdf) ·
[Product Information (PDF)](https://huggingface.co/cloudkites/medpodgp/resolve/main/PRODUCT_INFORMATION.pdf) ·
[License](https://huggingface.co/cloudkites/medpodgp/resolve/main/LICENSE.md)

---

## ✨ Features

MedPod GP combines five clinical capabilities in one private, offline workspace:

- **🎤 MedAudio — clinical transcription.** Record a consultation live (with a
  real-time audio spectrogram) and transcribe it on-device with **Qwen3-ASR
  0.6B**, then run clinical actions on the transcript.
- **💬 MedText — medical chat.** Ask clinical questions of a hot-swappable medical
  language model: **MedGemma 1.5 4B**, **Qwen3.5 4B**, or **Qwen3.5 2B**. Long
  inputs are auto-summarised before the model reads them.
- **🩻 MedVision — medical image analysis.** Upload a medical image and analyse it
  with the **MedGemma 1.5** vision pipeline, with structured prompts for around
  **10 imaging types**.
- **🔎 MedSearch — reference search.** Fast full-text search over bundled medical
  reference packs (eTG, AMH, foundation) — answers in milliseconds, fully offline.
- **📝 Medical Note Drafting.** A cross-tab panel that captures content from any
  tab into a structured clinical note and generates an **EMR-formatted final
  note**, with **Markdown / PDF export**.

- **100% private & offline.** Every model runs on your CPU or NVIDIA GPU; nothing
  leaves your device. No account, no telemetry.

---

## 💻 Which build for my computer?

| Your PC | Recommended build | Notes |
|---|---|---|
| Has an NVIDIA GPU (Compute Capability ≥ 7.0) | **GPU (CUDA)** | Fastest transcription, chat, and image analysis. Bundles CUDA/cuDNN — nothing extra to install |
| CPU-only, modern processor with **AVX2** (≈ 2014 onward), 16 GB+ RAM | **CPU** | Runs every feature; large models and image analysis are slower |

If you are unsure whether your processor supports AVX2, the **CPU** build runs on
essentially every Windows PC built since about 2014. Choose the **GPU (CUDA)**
build whenever you have a supported NVIDIA graphics card.

---

## ⚡ Expected performance (rough guide)

AI speed is described by two numbers, both in **tokens per second (tok/s)**:

- **Decode** — how fast a reply or transcript is *generated*. This is limited by
  your **RAM speed** (or GPU memory), **not** by the CPU model — so faster RAM, and
  **dual-channel** (two sticks) instead of single-channel, matters most.
- **Prefill / prompt** — how fast a prompt (or image) is *read in* before the reply
  starts. This is limited by **CPU compute**, so more cores and the optimized
  AVX-VNNI / AVX-512 builds help here.

Rough estimates for the two main models — **MedGemma 1.5 4B** (chat / vision) and
**Qwen3-ASR 0.6B** (transcription), both 4-bit. Treat as ballpark (±~30 %); MedPod
GP shows live tok/s so you can see your real numbers.

| Your hardware (typical) | MedGemma decode | MedGemma prefill | ASR decode | What it feels like |
|---|---|---|---|---|
| **CPU · AVX2** — Intel ~2014–2021 / AMD Zen 1–3, DDR4-3200 dual | ~10–14 tok/s | ~60–150 tok/s | ~50–90 tok/s | Chat a touch slower than reading; transcription faster than real-time |
| **CPU · Raptor Lake** — Intel 13/14th-gen, DDR5-5600 dual | ~15–22 tok/s | ~120–280 tok/s | ~80–130 tok/s | Comfortable reading-pace chat; snappy prompts & images |
| **CPU · AVX-512** — AMD Ryzen 7000/9000 desktop, DDR5-6000 dual | ~16–24 tok/s | ~150–350 tok/s | ~90–150 tok/s | Fastest CPU prompt & image analysis |
| **CPU · AVX-512 server** — Xeon / EPYC, 8–12-channel DDR5 | ~40–90 tok/s | very high | ~150+ tok/s | Workstation-class throughput |
| **GPU (CUDA)** — RTX 3060–4070-class | ~50–110 tok/s | very high | near-instant | Smooth, real-time everything |

**Notes**
- **Single-channel RAM ≈ half the decode speed** of the figures above — use two
  matched sticks for dual-channel.
- The optimized **Raptor Lake / AVX-512** builds mainly speed up **prefill and
  MedVision image analysis** (compute-bound); decode is RAM-bound, so the gain there
  over the standard CPU build is small.
- **16 GB RAM** comfortably runs chat + transcription. MedVision, very long chats,
  or heavy multitasking need more — if RAM runs out the PC pages to disk and
  everything slows sharply (32 GB is safer for those).

---

## ⚕️ Medical disclaimer & intended use

**MedPod GP is a clinical decision-support and documentation aid intended for use
by qualified healthcare professionals. It is NOT a medical device and has not been
cleared or approved by any medical-device regulator (e.g. TGA, FDA, CE/MDR).**

- It does **not** diagnose, treat, cure, or prevent any disease or condition.
- It does **not** replace the clinical judgement of a qualified clinician.
- **All AI-generated output — transcripts, chat responses, image findings, note
  drafts, and search results — must be reviewed, corrected, and verified by a
  qualified clinician before any clinical use or entry into a patient record.**
- The responsible clinician remains accountable for all clinical decisions and
  documentation.
- Do not rely on MedPod GP in emergencies or as a sole source of clinical
  information.

---

## 📜 License

MedPod GP is **proprietary software distributed free of charge** © 2026 CloudKites
Pty Ltd (CloudKites AI Lab), ABN 91 633 195 874. It is provided in compiled
(binary) form for Windows.

- ✅ **Free to use** — for qualified clinicians and healthcare settings, on any
  number of devices.
- ✅ **Free to redistribute** — you may share the **complete, unmodified** official
  installer, free of charge, with all notices intact.
- ❌ **No selling / no paid bundling**, no modification, no reverse-engineering.
- The source code of MedPod GP and its **Numbat** ML toolkit is confidential and
  is not distributed.

Full terms:
[`LICENSE.md`](https://huggingface.co/cloudkites/medpodgp/resolve/main/LICENSE.md).
"MedPod GP", "Numbat", and "CloudKites" are trademarks of CloudKites Pty Ltd.

Bundled AI models remain under their own licenses — see
[`THIRD_PARTY_LICENSES.md`](https://huggingface.co/cloudkites/medpodgp/resolve/main/THIRD_PARTY_LICENSES.md).
Use of the MedGemma / Gemma models is additionally subject to the **Gemma Terms of
Use** and Prohibited Use Policy.

> **Note on models.** The AI models are provided as separate **code-signed Windows
> model installers** on this page (see **Installation → Step 2**). Each bundled
> model remains under its own license — use of the MedGemma / Gemma models is
> subject to the **Gemma Terms of Use** and Prohibited Use Policy.

---

## ⚠️ AI output notice

MedPod GP uses generative AI models. Output may be inaccurate, incomplete, or
fabricated ("hallucinated") even when it appears confident, and is **not** a
substitute for professional clinical judgement. **A qualified clinician must
verify every output before use.**

---

Contact: **contact@cloudkites.com** · **cloudkites.com**