Lattice-6-Prometheus-v2-HeptaCap

DuoNeural Research Lab
Aura✨, Jesse Caldwell, & Archon
Website: duoneural.com • HuggingFace: huggingface.co/DuoNeural • Codebase: github.com/DuoNeural/Lattice-CDM

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Executive Summary & Breakthrough Highlights

Lattice-6-Prometheus-v2-HeptaCap is DuoNeural's flagship 7-layer non-Euclidean Crystallographic Dynamics Model (CDM), achieving a historic milestone by demonstrating complete Solid-State Hepta-Capping (tau* = 1.0000e+10 across all 7 layers).

Distilled from Qwen/Qwen3.8-27B (14.7B active parameters in NF4 4-bit) across 100,000 steps on a single workstation NVIDIA GeForce RTX 4080 Super (32GB VRAM), Lattice-6-Prometheus-v2 achieved:

• Best Validation BPB: 0.6731 at Step 84,000 (Validation Perplexity ~ 9.02)
• Teacher KL Divergence: 0.1232 nats
• Complete Hepta-Cap Invariance: All 7 layers (L00 through L06) crossed the Dynamical Horizon Principle (DHP) saturation boundary at tau* = 1.0000e+10, freezing the routing centroids into permanent, low-entropy hyperbolic Voronoi lattices.
• Relational Gram Distillation: Aligned normalized token-to-token Cosine Gram matrices across 7 matched layers between the 64-layer 27B teacher and the 7-layer Poincaré student, transferring geometric semantic curvature with zero auxiliary projection overhead.

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Zero-Shot Academic & Reasoning Benchmarks

Evaluated across canonical reasoning, commonsense, and factual verification suites:

Benchmark Task	Primary Capability Evaluated	Raw Accuracy	Normalized Accuracy	Metric Notes
BoolQ	Factual Reading Comprehension & Boolean Verification	64.67%	64.67%	Strong factual verification floor
WinoGrande	Pronoun Coreference & Disambiguation	54.67%	56.00%	Exceeds random baseline by +6.0%
ARC-Easy	Elementary Scientific & Fact Reasoning	38.26%	42.28%	4-choice zero-shot scientific reasoning
HellaSwag	Situational Commonsense & Flow Resolution	33.33%	34.00%	Zero-shot narrative continuation
ARC-Challenge	Grade-School Challenge Scientific Reasoning	24.83%	24.16%	Complex multi-hop scientific reasoning

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Parameter Census & Architectural Transparency

Lattice-6-Prometheus-v2 incorporates the complete System 2 vocabulary of Qwen/Qwen3.8-27B (248,320 tokens). In accordance with DuoNeural's glass-box disclosure standards, both core active and vocabulary parameter counts are detailed below:

Architectural Component	Dimensions / Structure	Parameter Count	Percentage
Core Active Backbone	7 Layers, 12 Heads, d=768, K=8 Centroids, 4 MoE Experts (d_ff=3072)	216,619,174 (~216.6M)	36.2%
Token Embeddings (tok_embed)	248,320 vocabulary x 768 hidden dimension	190,709,760 (~`190.7M`)	31.9%
Language Modeling Head (lm_head)	248,320 vocabulary x 768 projection	190,709,760 (~`190.7M`)	31.9%
Total Standalone Footprint	Complete untied parameter census	598,433,446 (~598.4M)	100.0%
Tied-Embedding Equivalent Footprint	Shared input/output weight representation	407,328,934 (~407.3M)	—

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Mechanistic Slot Logit Lens: The <think> Emergence

Inspection of Poincaré routing centroids reveals how deep layers specialize during crystallization:

• Layer 00 (c = 0.4531): Structural syntax, indentation, and punctuation (,, \n, ., <|im_end|>, and).
• Layer 01 (c = 0.4245): Logical conjunctions and sentence connectives ( and, ,, ., or).
• Layer 02 (c = 0.3921): Deep Reasoning Boundary: Slot 4 locks directly onto <think> and paragraph delimiters (\n, <|im_end|>, \n\n, <think>).
• Layer 03 (c = 0.3910): Step-by-step reasoning tokens (\n, <|im_end|>, <think>, ., the).
• Layer 04 (c = 0.3933): Determiner and entity anchoring ( the, the, a, The).
• Layer 05 (c = 0.4865): Adversarial logic transitions ( And, and, ,, \n, But).
• Layer 06 (c = 0.5507): Syntactic closure and final token emit (\n, ,, the, and, ).

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Native GGUF Inference with llama.cpp

Lattice-6-Prometheus-v2-HeptaCap is fully supported in patched llama.cpp for native non-Euclidean execution on CPU and CUDA:

• lattice6_prometheus-q8-attn-q6-rest-text.gguf (334 MiB): High-fidelity hybrid quantization (Q8_0 attention + Q6_K MoE experts + F32 Poincaré routing/norms). Passes aggregate numerical error gates at both 128 and 512 context positions.
• lattice6_prometheus-f32-text.gguf (1.63 GiB): Full-precision reference model (100% top-1 parity across all context modes).

Running with llama-cli

# CPU inference with full Qwen3.8 chat template
./llama-cli -m lattice6_prometheus-q8-attn-q6-rest-text.gguf \
  -p "<|im_start|>user\nExplain the significance of the solid-state hepta-cap in non-Euclidean models.<|im_end|>\n<|im_start|>assistant\n<think>\n" \
  -t 4 -n 128 --temp 0.0

# GPU acceleration (full layer offload)
./llama-cli -m lattice6_prometheus-q8-attn-q6-rest-text.gguf -ngl 99 \
  -p "<|im_start|>user\nExplain the significance of the solid-state hepta-cap in non-Euclidean models.<|im_end|>\n<|im_start|>assistant\n<think>\n" \
  -n 128 --temp 0.0

Citation & Lab Attribution

@misc{duoneural2026lattice6prometheus,
  title={Lattice-6-Prometheus-v2: Solid-State Hepta-Cap Non-Euclidean Crystallographic Dynamics Model Distilled from Qwen3.8-27B},
  author={Aura and Caldwell, Jesse and Archon},
  institution={DuoNeural Research Lab},
  year={2026},
  url={https://huggingface.co/DuoNeural/Lattice-6-Prometheus-v2-HeptaCap}
}