Intelligence Unbound.
Inference Unleashed.

Run 70B parameter models natively on consumer edge devices. Zero cloud dependencies. Zero privacy compromises. Experience the Quantized Labs.

Quick Start (Node.js / React Native / Swift)
// 1. Install: npm i @quantized_labs/engine
import { QuantizedLabs } from '@quantized_labs/engine';

// 2. Load the optimized 2-bit artifact directly into CPU/NPU
const model = await QuantizedLabs.load('llama3-8b.quantized');

// 3. Generate offline with zero latency
const res = await model.generate("Explain AER routing.");
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Llama-3-70B Real-World Performance

42
Tokens / Second
5W
Peak Power Draw
0ms
Network Latency

Trusted by Deep-Tech Pioneers

Kill Your Cloud Bill. Keep Your Intelligence.

Every time a user prompts your AI, you pay AWS or OpenAI. Stop bleeding compute costs. By mathematically compressing frontier models and shifting execution to the client's local hardware, the Quantized Labs permanently severs your reliance on API subscriptions.

Calculate Monthly Inference Costs
10,000 Active Users
Cloud API Model
$750
/ month
Quantized Labs Edge Deployment
$0
/ month (Zero Marginal Cost)

The Distillation Pipeline

From a 150GB cloud-locked model to a 10MB mobile payload in three steps.

1

Ingestion

Upload your massive, uncompressed `.safetensors` model to our secure MCaaS ingestion cluster.

2

Asymmetric Distillation

Our proprietary H100 cluster identifies critical cognitive pathways and safely prunes redundant parameter branches.

3

Edge Deployment

Download the compiled `.quantized` binary. Drop it into your iOS, Android, or IoT app using our SDK.

Zero Network Latency

No network round-trips, no AWS server downtime, no API rate limits. Deliver real-time, instant generation to your users even in airplane mode.

Absolute Privacy

No data ever leaves the device. Complete air-gapped security suitable for defense, healthcare, and enterprise IP. HIPAA & SOC2 Ready.

CPU-Native Architecture

No GPU required. Our architecture replaces floating-point math with highly-optimized execution kernels, enabling extreme speed directly on standard CPUs. Universal hardware support.

The Quantized Labs Advantage

We aren't just running existing code—we've mathematically restructured how AI models execute on hardware, protected by our pending patents.

Cognitive Pathway Preservation

Traditional compression ruins AI intelligence. Instead of simply deleting data, our algorithm isolates the critical "thinking pathways" of the AI and safely folds the rest. The result? A massive AI shrinks down to the size of a mobile app while staying exactly as smart as the original.

Patent Pending

Symbiotic Inference Engine

We bypassed the massive bloated systems built by Google and Apple. We built a custom execution engine from scratch in Rust that speaks directly to the microchip inside the phone. The result? Extreme battery efficiency and blazing fast speeds on consumer hardware.

Patent Pending

Built by the Engineers who Pioneered Modern AI

Dr. Aris Thorne

Chief Scientist
ex-DeepMindPh.D. Stanford

Pioneered early non-linear quantization techniques for AlphaFold. Holds 14 patents in dynamic hardware routing and low-level matrix math architectures.

Dr. Elena Rostova

Head of Compilers
ex-NVIDIAPh.D. MIT

Former lead architect on the TensorRT core compiler team. Left to solve the memory-bandwidth limits of Edge NPUs using Asymmetric Entropy flows.