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Documentation Index

Fetch the complete documentation index at: https://docs.gamerhash.com/llms.txt

Use this file to discover all available pages before exploring further.

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).

Before you start

Hardware check

10/11, 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).

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.

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.

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.

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.

5. Opt in to earn (optional)

If you want to share idle GPU power for GUSD:
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.

Troubleshooting

Click More infoRun 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.
Possible reasons: too few hours of uptime, GPU class limits the workload pool, network demand is low at the moment. Check the in-app dashboard and Medium community updates for current network demand.

Next

Earn with GPU sharing

Deeper walk-through of the earning module.

Modules

Tour every module the app ships.