coolingcube-q 0.1.1

Quantization feasibility analyser — is your quant NFF for coding, math, reasoning or chat?

coolingcube-q

Quantization feasibility analyser. Takes your KLD and top-1 agreement measurements and tells you whether your quant is safe to deploy for coding, math, reasoning or chat.

Install

pip install coolingcube-q

Usage

from coolingcube_q import analyse_quant

# remichu_sm's real measurement: Step3.7 5.05bpw
result = analyse_quant(
    kld=0.0056,
    top1_agreement=0.9594,
    task="coding",
    bpw=5.05,
    model_params_b=27
)

print(result["verdict"])       # Feasible — safe to deploy
print(result["recommendation"])

Get your measurements

From ExLlamaV3 eval scripts:

# KLD vs BF16 base
python eval/model_diff.py -ma ./quantized_model -mb ./bf16_model -r 5

# Perplexity across bitrates
python eval/compare_q.py --help

Tasks

• coding — code generation, agentic coding (most demanding)
• math — mathematical reasoning
• reasoning — thinking models, chain of thought
• general — mixed use
• chat — conversation (most forgiving)

Check all tasks at once

coolingcube-q --kld 0.0056 --top1 0.9594 --bpw 5.05 --model 27 --all-tasks

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