🖥️ Google Cloud Gemini Mesh • Nomos Deterministic Substrate Core (Go 1.24) • NixOS (headless-ai)
Debt Items Audited 373 Items / 26 Cycles
Subtasks Closed In Flight 80 Completed
Human Intervention 0% (Autonomous)
Compile-Time DoD Gates 39 Gates (100% Pass)
Turn Latency ~230ms / turn
We unleashed the Nomos Code Swarm orchestrator powered by Google Gemini 3.5 Flash-Lite to autonomously burn down technical debt across the Nomos multi-repo ecosystem. Bounded by Nomos's 39 compile-time Definition of Done (DoD) quality gates and dual-core cognitive scaffolding, the swarm achieved 100% gate compliance, zero AST regressions, and sub-250ms per-turn latency across topological cycles with 0% human intervention.
🖥️ NVIDIA GeForce RTX 4080 (16,376 MiB) • Intel Core i5-12600KF • NixOS (headless-ai)
Polyglot Pass@1 100% (5/5)
Mean Turn Velocity 6.2 Turns
Mean Exercise Latency 32.5s / Lang
Target Hardware RTX 4080 (16GB)
We benchmarked the autonomous Nomos Code Tier 2 Sovereign Engine across the Aider Polyglot Multi-Language Benchmark, evaluating autonomous code editing, search/replace precision, and compiler verification across Go, Python, Rust, JavaScript, and C++. Nomos Code achieved 100% Pass@1 accuracy in 6.2 mean turns on a local RTX 4080 (Qwen3.8-27B).
🖥️ NVIDIA GeForce RTX 4080 (16,376 MiB) • Intel Core i5-12600KF • NixOS (headless-ai)
Pass@1 Accuracy 100% (5/5)
Mean Turn Velocity 6.4 Turns
Mean Problem Latency 54.4s / Inst
Target Hardware RTX 4080 (16GB)
We benchmarked the autonomous Nomos Code Tier 2 Sovereign Engine across the LiveCodeBench Contamination-Free suite, testing algorithmic synthesis, asymptotic time complexity, and dynamic test harness repair across LeetCode, AtCoder, and Codeforces challenges. Nomos Code achieved 100% Pass@1 accuracy across Easy, Medium, and Hard difficulty tiers on local RTX 4080 silicon.
🖥️ NVIDIA GeForce RTX 4080 (16,376 MiB) • Intel Core i5-12600KF • NixOS (headless-ai)
Resolution Parity 60.0% (3/5)
Local Turn Efficiency 11.2 Turns (vs 12.6)
Local VRAM Footprint 15.4 GB / 16.0 GB
Target Hardware RTX 4080 (16GB)
We benchmarked the autonomous Nomos Code Tier 2 Sovereign Engine across the SWE-bench Verified Golden Mini Suite, pitching local workstation inference (Qwen3.8-27B on a single RTX 4080) against Google's frontier Gemini 3.7 Flash with 8k Thinking. Local execution achieved 100% resolution parity (60.0% accuracy) in 11.2 mean turns (vs 12.6 turns on Cloud Gemini post-NOM-647 optimization) at $0 marginal inference cost.
🖥️ NVIDIA GeForce RTX 4080 (16,376 MiB) • Intel Core i5-12600KF • NixOS (headless-ai)
Generation Speed 38.8 tok/s
GPU VRAM Offload 100% (99/99 Layers)
Time to First Token ~277 ms
Context Window 2x 16k Slots
As part of the Nomos Tier 2 Sovereign Engine rollout, we benchmarked Qwen3.8-27B (Dense, Q3_K_M) on a dedicated workstation equipped with an RTX 4080 (16GB). Through targeted memory optimization, 100% of the 27-billion-parameter model layers are offloaded into GPU VRAM with zero PCIe memory spillover, delivering native chain-of-thought reasoning and autonomous tool dispatching at ~38.8 tokens/second.
