🧮 Paretrix GGUF quantizations of openbmb/MiniCPM5-2B with DSpark draft

Model MiB PPL ΔPPL KLD RMS Δp top-p Pareto
Q8_0 (stock) 2556 11.9393 +0.0181 0.0015 0.99% 97.8% ★
Fidelity-48pc 2309 11.9598 +0.0386 0.0033 1.47% 96.8% ★
Q6_K-imx (stock) 1974 11.9724 +0.0512 0.0059 1.91% 95.9% ≈ Precision-42pc (−0.0002 · −1 MiB)
Precision-42pc 1973 11.9678 +0.0466 0.0057 1.89% 96.0% ★
Q5_K_M-imx (stock) 1724 12.0905 +0.1693 0.0195 3.58% 92.8% < Quality-36pc
Quality-36pc 1723 12.1180 +0.1968 0.0175 3.43% 93.3% ★
Compact-33pc ⭐ 1593 12.2219 +0.3007 0.0427 5.12% 89.2% ★
Mini-30pc 1446 12.3731 +0.4519 0.0672 6.53% 86.7% ★
IQ4_XS-imx (stock) 1358 12.3977 +0.4765 0.0722 6.69% 86.9% ★
Nano-27pc 1306 12.6530 +0.7318 0.0848 7.26% 85.7% ★
IQ3_M-imx (stock) 1170 13.9101 +1.9889 0.2027 11.74% 78.6% < Pico-24pc
Pico-24pc 1154 13.9155 +1.9943 0.1719 10.52% 79.3% ★
Femto-21pc 1016 15.2794 +3.3582 0.2918 14.25% 73.9% ★

ℹ️ About Paretrix Quantization Suite

Paretrix is an empirical, activation-aware quantization suite for GGUF language models and speculative decoding modules.

Pareto + Matrix → Paretrix. Each tier is priced so that no better trade exists at that compression. The suite measures real activation sensitivity (ΔKLD/MiB) per tensor class through llama-imatrix, learns rate tables from cross-architecture campaigns (THE MATRIX), and allocates bitwidths under exact budget targets: flat recipes where uniformity wins, rate-calibrated knapsack where heterogeneity pays.

Standard uniform quantization applies one bitwidth family across the whole network. Paretrix reads the model's own activation field (which classes are expensive to cut, which are nearly free, and where depth matters), then spends the budget where measurements show the greatest return.

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