Sibacus
Live Inference — Try the Workbench

Run Any AI Model.
6.6× Less Energy.

The Sibacus Transform replaces floating-point multipliers with bit-shifts and integer adds. Same model quality. Fraction of the power. No GPU required.

Energy Saved vs GPU (live counter)
0.0 mJ across 0 tokens

Validated Across 8 Models From 4 Continents

🇺🇸
Meta
Llama 3.1
🇺🇸
Microsoft
Phi-3
🇺🇸
Google
Gemma
🇫🇷
Mistral AI
Mistral Small 3
🇨🇳
Alibaba
Qwen 2.5
🇨🇳
DeepSeek
DeepSeek R1
🇦🇪
TII
Falcon
6.6×
Energy Reduction
per token vs FP32 MAC
2.7×
Model Compression
at K=2 BSA
≤+0.08
Perplexity Delta
near-lossless quality
$0.94/hr
Instance Cost
vs $30/hr H100 GPU

How It Works

Drop-in replacement for standard inference. Three steps to sovereign-grade efficiency.

1

Load Any Model

Bring your HuggingFace model — Llama, Mistral, Qwen, DeepSeek, or any transformer architecture.

2

Transform

The Sibacus Transform converts every weight to shift-and-add format. Zero multipliers. Near-lossless quality.

3

Deploy

Serve via OpenAI-compatible API on commodity ARM CPUs. 6.6× less energy. 32× cheaper than H100.

Sovereign Compliant

Built for Data Centers

Meet power budget constraints without sacrificing model quality. Sibacus enables data centers to run production AI inference within regulatory thermal envelopes — critical for sovereign deployments in power-constrained regions.

  • ✓
    DC-CFA Compliant — 5-6× lower power per rack vs GPU baseline
  • ✓
    Model Agnostic — US, European, and Chinese models all supported
  • ✓
    OpenAI-Compatible API — Drop-in replacement for existing infrastructure
Cost Comparison per 1M Tokens
H100 GPU (p5.xlarge)
$1.67
Sibacus Transform (Graviton4)
$0.05
33× cost reduction

See It Running. Right Now.

No signup. No API key. Just pick a model and start chatting. Every token is powered by the Sibacus Transform.