MYGPU
Detecting your GPU…

Not your GPU,
not your AI.

MYGPU runs large language models entirely on your own hardware, inside the browser. No servers. No accounts. Zero data egress.

Local nodelive
Adapter—
Architecture—
Max buffer—
FP16 shaders—
Data egress0 bytes
0 B
Prompt data sent to any server
100%
Inference on your device
3
Open models, switchable live
Offline
Keeps running with no network
Product

A full AI terminal. Running on silicon you own.

Load a model once and it lives in your browser. Disconnect from the internet and keep working — there was never a server to lose.

mygpu.fun/terminalNetwork offLlama 1B

On-device inference

WebGPU runs the model on your graphics card. Every token is computed locally.

Works offline

After the first load, the model runs with your network completely disconnected.

Three open models

From a 360M model for speed to a 3B model for depth. Switch without reloading.

Live telemetry

Tokens per second, latency, context size and egress — measured, not promised.

Architecture

Four stages. None of them leave your machine.

01

Weights

Open model weights, 4-bit quantized, downloaded once and cached in your browser.

q4f16_1
02

Kernels

Compiled WGSL compute shaders dispatch matrix operations straight to your GPU.

MLC · WebGPU
03

Memory

The KV-cache and activations live in your VRAM. We don't operate any servers.

local VRAM
04

Output

Tokens stream into your tab. Close it and the session is gone. Nothing is logged.

egress: 0 B
Principles

No server. No account. No kill switch.

01 — Custody

Self-custody, for intelligence.

You hold your keys on your own device. Your AI should follow the same rule.

02 — Resilience

Nothing to shut down.

If this website went offline tomorrow, the model already on your machine would keep running.

03 — Ownership

Built on Solana.

$MYGPU is the community behind private, self-hosted AI. Not your GPU, not your AI.

Get started

Your GPU is ready.

No sign-up. Open the terminal, load a model, and start working privately.

Launch terminalView the engine on GitHub