# methodology

OGM scores are transparent, reproducible, and computed only within the open-weights set — a score says how a model compares to other open-weights models, not to closed frontier models. Three principles:

## overall weights

signalweight
aa_intelligence0.50
arena_elo0.30
bench_composite0.20

## coding weights

signalweight
aa_coding0.25
aider_polyglot0.25
arena_elo_code0.15
swe_bench_verified0.35

## agentic weights

signalweight
swe_bench_verified1.00

## signal normalization

## data flow

A pipeline pulls ten sources daily (Hugging Face, OpenRouter, Artificial Analysis, LLM Stats, LiveBench, LMArena, Epoch AI, SWE-bench, Aider, LiteLLM), resolves every record to a canonical model through a hand-curated registry, and publishes the merged dataset — the same JSON this site and the ogm CLI read, public at /data/v1/. Provider prices refresh every 6 hours. Failed sources fall back to their last snapshot and are marked stale in the footer.

The scoring implementation lives in the repo as pure, golden-tested functions.