🌲 BlackForest Studio — High-Performance AI Suite

🌿 Project Kalos: Microsecond Memory Recall Profiler

Demonstrating 0.465ms constant-time memory recall, 99.8% VRAM reduction, and 15.16μs spiking sentry reflexes.

1. Select LLM Model Architecture & Scale:

2. Dialogue Context History Depth: 16,000 tokens

Metric	Standard LLM Context	🌿 Kalos C/CUDA Engine	Kalos Advantage
Memory Recall Latency (TTFT)	20,441.60 ms (20.44s)	0.465 ms (0.00046s)	43,960x Faster
Recall Time Complexity	O(N) Degradation	O(1) Constant-Time CUDA	Zero Prefill Lag
SAM Template Buffer VRAM	16.38 GB	2.50 MB	99.8% VRAM Saved
SNN Reflex Sentry VRAM	N/A (Text Only)	64.0 MB (4.19M Neurons)	15.16 μs Spiking Reflexes

Simulating dynamic N ↔ M bi-directional norm-preserving phase harmonic vector projections.

1. Select Source Modality & Dimension (N):

2. Select Target LLM & Dimension (M):

3. Sequence Token Length: 16 tokens

Projection Parameter	Source Space (N)	Target Space (M)	Fidelity Signal
Tensor Dimension Shape	[1, 16, 3584]	[1, 16, 5120]	Lossless Projection
Mean Vector Signal Norm	59.8665	59.8665	100.0% Energy Preserved
CUDA Execution Engine	libchiasm.so (Microsecond Subspace Harmonics)		Zero GGUF Crash