Welcome to Your TT-QuietBox 2

Four Blackhole chips · 480 Tensix cores · 128 GB GDDR6 · no API keys required

From open source models to local agents to custom kernels and infinite generative art. Welcome to your TT-QuietBox 2.

💻 Open TT-Studio ⚡ Install VS Code Toolkit 📚 Browse all lessons 📋 Setup guide

CARD 0

BH·0

BH·1

Samtec cable · inter-card link

CARD 1

BH·2

BH·3

🗨️

Chat with AI

Private LLM inference — 32B & 70B scale

Start here TT-Studio — browser UI, one-click model deploy, pre-installed

Models Llama-3.3-70B ~14s/response · Llama-3.1-8B fast · full catalog ↗

API TT-Inference-Server — OpenAI-compatible endpoint, pre-installed

Monitor TT-Toplike — watch cores during inference

→ Coding Assistant with Aider

🎬

Generate Video & Images

Text-to-video, image-to-video, stills

Start here TT-Studio — deploy any model with one click, pre-installed

Gallery TT-Local-Generator — queue, gallery, TT-TV kiosk mode

Video Wan 2.2-14B ~6 min/5-sec clip

Image FLUX.1-dev high-quality stills

Prompts ✨ Inspire me — prompt ideas from a small on-device model

→ Video Generation on QB2

🤖

Build AI Agents

Tool calling, multi-agent, stateful pipelines

Best model Llama-3.3-70B — best for agents

Frameworks smolagents · CrewAI · OpenAI Agents SDK

Demos Web research · codebase nav · multi-role pipelines · stateful dungeon master

Privacy Data never leaves the machine — architecture, not policy

→ Local AI Agents on QB2

⚡

Hack the Hardware

There’s a real computer in here — boot Linux, write kernels

Boot tt-bh-linux — run Linux on 16 RISC-V cores inside the chip

Demos Conway’s Game of Life · Zork on TT hardware

Kernels tt-lang — Python DSL for Tensix kernels · TT-Metalium — C++ dispatch

Explore tt-tiny — George Hotz’s minimal bare-metal Python exploration

→ Cookbook: Game of Life → Intro to tt-lang

🔬

Explore the Architecture

TT-Toplike, Particle Life, TT-Metalium

Watch TT-Toplike — Starfield, Memory Castle, Memory Flow, Arcade

Run Particle Life Simulator on 4× chips — emergent complexity

Compile TT-Forge — bring any PyTorch or ONNX model to the hardware, 100+ supported

Program TT-Metalium — C++ kernels on RISC-V cores in the 2D mesh

Discover TT-Awesome — community apps, demos, libraries, and write-ups

Lessons CS Fundamentals series · Particle Life walkthrough

Train TT-Blacksmith — fine-tune or train from scratch on 4× Blackhole

→ CS Fundamentals → Particle Life → Custom Training

Tool	What it does	Where
TT-SMI	Hardware status and telemetry snapshot	Pre-installed
TT-Studio	Web GUI for deploying and chatting with AI models — handles all setup automatically, deploy models in one click. Gated models (e.g. Llama) require a Hugging Face token.	Pre-installed — run `tt-studio`
TT-Inference-Server	OpenAI-compatible model serving endpoint	Pre-installed at `~/.local/lib/tt-inference-server`
TT-Toplike	Real-time hardware visualization — power, temperature, core activity	docs.tenstorrent.com/tt-toplike
TT-Local-Generator	Local video and image generation queue and gallery	docs.tenstorrent.com/tt-local-generator
TT-VSCode-Toolkit	Guided lessons and architecture walkthroughs, validated on QB2	docs.tenstorrent.com/tt-vscode-toolkit
TT-Forge	MLIR compiler frontend — run PyTorch, ONNX, and JAX models on QB2 hardware, 100+ models supported	docs.tenstorrent.com/tt-forge
TT-Metalium	Low-level Tensix programming — C++ kernels on RISC-V cores	firdovsimammedovk.github.io/tt-metal-sandbox/tt-metalium
TT-Blacksmith	Optimized training recipes — fine-tune and train models from scratch on QB2	firdovsimammedovk.github.io/tt-blacksmith-sandbox

Hardware setup not finished? Start with the setup guide — unboxing, first login, verifying chips with tt-smi, and launching your first model. Need help? Raise a support request.

Want to try before you install? console.tenstorrent.com — run LLM inference, image and video generation in-browser, backed by Tenstorrent hardware.