Open Methodology. Strict Verification.
We publish our analytical models, benchmark rubrics, and limiting physical constraints openly — advancing transparent, verifiable engineering for personal computing.
Published Notes & Findings
Native Quantization & MoE Checkpoint Feasibility
Rigorous analysis of modern open-weight mixture-of-experts architectures. Detailed examination of native low-bit training formats (MXFP4/MXFP8) and post-training compression boundaries.
Multi-Head Latent Attention & Hybrid Linear-Sparse Scaling
Comparative evaluation of joint KV cache compression techniques and linear attention mechanisms to support million-token context windows for comprehensive repository understanding.
Memory Bandwidth Modeling for Interactive Local Autonomy
First-principles mathematical modeling relating token generation velocity to bus bandwidth, cache hit ratios, and physical memory hierarchies under consumer desktop power constraints.
Holistic Multi-File Autonomous Engineering Benchmarks
Standardized multi-dimension evaluation rubric scoring architecture synthesis, test generation, live debugger interactions, and long-horizon autonomy on production-grade codebases.
The 7-Stage Evidence Hierarchy
Grafion Labs operates on a strict verification hierarchy where research hypotheses and engineering targets are never conflated with accomplished results.