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This walks you from downloading the AI App to your first chat completion. Time: 5 minutes plus model download (which happens in the background and varies by model size).

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Before you start

Hardware check

11, NVIDIA RTX with 8 GB+ VRAM, recent driver. Full breakdown in Hardware requirements.

Disk space

~30 GB free for downloaded models. More if you keep many models cached.

GamerHash account

Created during install — email or Google login.

Network

Broadband. Initial model downloads are large (4–20 GB depending on model).

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1. Download

1

Open the download page

Go to gamerhash.com/en/app-download and click Download GamerHash AI. The installer is .exe and signed.
2

Run the installer

Double-click the downloaded .exe. Windows may ask for admin permission — accept. The installer is signed by GamerHash; if Windows SmartScreen warns, click More info → Run anyway.
3

Pick install path

Default is fine for most users. If you have multiple drives, pick the one with the most free space — model files end up here.

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2. First run

1

Sign in or create an account

On first launch you’ll be prompted. Sign in with Google is the fastest path. Email + password also works.
2

Run the GPU benchmark

The app benchmarks your GPU once to size workloads correctly. Takes ~1 minute. You won’t need to repeat this unless you change hardware.
3

Pick your first model

The Model Center opens. For a first chat, pick any model marked as a fit for your GPU (each model shows a VRAM-fit badge). Click Download — progress shows in the bar.
First model download is the slowest step. Smaller text models (~5 GB) download in 5–15 minutes on a typical home connection. Image and video models can be 10–20 GB.

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3. Your first chat

1

Open the Chat module

From the dashboard, click Chat. The model you just downloaded should be selected.
2

Send a prompt

Type a question and hit Enter. First response includes a model warmup — subsequent responses are faster.
3

Inspect the response

The response streams token-by-token. Generation runs entirely on your GPU; nothing is sent to a third-party cloud.

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4. Try image generation

1

Switch to the Image module

From the dashboard sidebar, pick Image Generation.
2

Pick a model

For 8 GB GPUs, Sana Sprint is a good first choice — fast and high quality. For 12 GB+, try FLUX.1 Schnell.
3

Generate

Type a prompt, click Generate. Output appears in the gallery; right-click to save or copy. Images are stored locally only.

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5. Opt in to earn (optional)

If you want to share idle GPU power for GUSD. Earning has a higher hardware bar than local use and runs on approved device types — check hardware requirements first. If yours isn’t approved yet you go on the waiting list, and the module switches itself on later.
1

Open the earning module

Sidebar → Earning. Read the explanation, then toggle the module on.
2

Leave it on when you're not gaming

Earning workloads take the full GPU and VRAM, so you can’t earn and game at the same time. Launching a game pushes the module out automatically; close the game and earning resumes on its own.
3

Watch GUSD accrue

Workloads start dispatching to your GPU as the queue allows. The dashboard shows live earnings per hour.

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Troubleshooting

Click More info → Run anyway. The installer is signed by GamerHash sp. z o.o. — verify the publisher in the certificate dialog.
Almost always a driver issue. Update to the latest NVIDIA Studio driver, reboot, retry. If it still fails, try the Game Ready driver. Report persistent failures in Discord #support with your GPU model.
Pause and resume from the Model Center. If it keeps stalling, check disk space and disable any aggressive antivirus. Some AVs scan multi-GB files extremely slowly.
First response loads the model into VRAM (cold start). Subsequent responses are fast. If chat is consistently slow, your GPU may be hitting VRAM limits — switch to a smaller quantized variant of the same model.
First check whether your device type is approved for earning at all — if it isn’t, you are on the waiting list and nothing is dispatched, however long you stay online. If it is approved, the usual causes are a narrow workload pool for your GPU class or low network demand at the moment. Check the in-app dashboard and the Medium community updates.

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Next

Earn with GPU sharing

Deeper walk-through of the earning module.

Modules

Tour every module the app ships.