Lade Stack
Infrastructure-Grade AI CLI

Sovereign AI Infrastructure for Developers.

Deploy, route, and control open-source LLMs on your own GPU infrastructure. Zero vendor dependency. Full data sovereignty.

Launching SoonView Architecture
lade-cli v0.1.0
p2p: 12ms
Philosophy

Why Lade Stack Exists

The current AI tooling landscape forces developers into vendor lock-in, unpredictable costs, and zero control over their infrastructure.

No API Vendor Lock-in

Run any open-source model on your own infrastructure. Switch models without changing a single line of code.

Predictable Cost at Scale

Fixed GPU costs instead of per-token billing. Run thousands of requests at a fraction of the API price.

Privacy-First Architecture

Your code never leaves your infrastructure. Full data sovereignty with zero external telemetry.

Multi-Model Routing

Intelligent routing across multiple models based on task type, context length, and cost optimization.

CLI-Native Workflow

Built for developers who live in the terminal. No browser tabs, no context switching.

Architecture

How It Works

From your terminal to GPU-accelerated inference. Every layer is designed for developer control and operational transparency.

DeveloperCLI ParserRouterModel PoolGPU VMs
01DeveloperCLI command input
02CLI ParserContext-aware parsing
03RouterIntelligent model selection
04Model PoolMulti-model inference
05GPU VMsHardware-accelerated compute
Models

Multi-Model Support

Route tasks to the best model for the job. Each model is optimized for specific workloads and runs on your own infrastructure.

Qwen

Code Generation
coding

High-performance code generation and completion. Optimized for multi-language development with strong reasoning capabilities.

DeepSeek

Debugging & Reasoning
reasoning

Deep chain-of-thought reasoning for complex debugging, architecture review, and multi-step problem solving.

GLM

Multilingual Reasoning
multilingual

Strong multilingual capabilities with robust reasoning across natural language understanding tasks.

Kimi

Long Context Analysis
128k-context

Extended context window support for analyzing large codebases, documentation, and complex specifications.

Infrastructure

Production-Grade Infrastructure

Deploy on any cloud provider with GPU support. Optimized for performance, cost, and operational reliability.

GPU Virtual Machines

Deploy on AWS, GCP, or any cloud provider with GPU support.

Quantization Engine

4-bit and 8-bit quantization for optimal memory efficiency.

Docker Containerization

Pre-built containers for instant deployment and reproducibility.

Kubernetes-Ready

Helm charts and manifests for production orchestration.

Model Caching

Persistent model cache with intelligent preloading strategies.

CLI Launching Soon

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