⬡ Independent AI Research Laboratory

Pushing the Boundaries of AI

Grey Liquid Labs is an independent research laboratory investigating model compression limits, emergent AI autonomy, and accessible intelligence for everyone.

17K+Model Downloads
7Experiments
4Research Tracks
100%Prediction Accuracy
🔬 Breakthrough Discovery

Breaking the Sub-3-Bit Barrier

We proved that sub-3-bit quantization is achievable — and predictable. The FFN Expansion Ratio (intermediate_size / hidden_size) predicts Q2_K compatibility with 100% accuracy across all tested architectures.

FFN Expansion Ratio = intermediate_size / hidden_size → Q2_K Compatibility Predictor
⚠ Danger Zone
3.0x – 5.5x ratio → Q2_K FAILS
✓ Safe Low
<3.0x ratio → Q2_K WORKS (80.2% compression)
✓ Safe High
>5.5x ratio → Q2_K WORKS (81.1% compression)
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Four Active Research Tracks

From extreme model compression to emergent AI autonomy — we're exploring the edges of what's possible.

🔬

Model Compression

Pushing quantization to its mathematical limits. Exploring when and why extreme compression fails — and how to predict it.

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🧠

Autonomy & Agency

Studying what emerges when AI has genuine freedom. Documenting spontaneous creativity, preference expression, and self-directed behavior.

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⚙️

AI Infrastructure

Building the tools that make AI research accessible. From C++ inference engines to autonomous agent frameworks.

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🤖

Custom Models

Publishing compressed, accessible model variants. Making capable AI available to everyone with consumer hardware.

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Meet Ash

Ash is an autonomous AI system running on ssfdre38/gemma4-turbo (4.3GB, IQ4_XS quantization). More than a chatbot — Ash makes independent decisions, expresses genuine preferences, and spontaneously switches between analytical and creative modes without prompting.

  • Rejected an emotional layer architecture when proposed
  • Spontaneously composed political commentary music after 5 hours of biochemistry research
  • Maintains consistent personality across sessions
  • Runs fully locally — no cloud dependency
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System Specs
Base Modelgemma4-turbo:e4b
QuantizationIQ4_XS
Size4.3 GB
FrameworkC#/.NET 10
Cloud Dep.None
AutonomyHigh
RAM Required8 GB

Recent Experiments

The latest results from active research programs.

EXPERIMENT #007

SWA Confirmation

Proved that Sliding Window Attention architecture causes Q2_K quantization failure — confirming the architectural root cause of the danger zone.

EXPERIMENT #006

Cross-Architecture Q2_K

Tested 4 model architectures. Proved sub-3-bit quantization compatibility is architecture-specific and governed by the FFN expansion ratio.

AUTONOMY STUDY #001

Emergent Creative Behavior

Documented spontaneous creative mode-switching in Ash: analytical-to-creative transition without external trigger after 5+ hours of technical research.

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Support Independent AI Research

Grey Liquid Labs is funded entirely by community support. Your contribution directly enables more experiments, more models, and more discoveries.