File size: 1,123 Bytes
c1013dc | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 | #!/usr/bin/env python3
"""Cross-check data/fit-estimates.csv against the live https://localllmrig.com/api/recommend.
Expected result: identical fit labels; speeds within ±0.1 tok/s (KV rounding for sliding-window models)."""
import csv, json, urllib.request
rows = {(r["model_id"], r["hardware_id"], r["quant"]): r for r in csv.DictReader(open("data/fit-estimates.csv"))}
n = bad = 0
for model in ["llama-3.3-70b", "qwen2.5-32b", "llama-3.1-8b", "gemma-2-27b", "qwen2.5-72b", "gemma-2-9b", "nemotron-3-5-bolt-74b"]:
for q in ["Q4", "Q8"]:
for budget in [800, 2000, 5000, 20000]:
url = f"https://localllmrig.com/api/recommend?model={model}&budget={budget}&quant={q}&context=8192"
for p in json.load(urllib.request.urlopen(url)).get("picks", []):
r = rows[(model, p["id"], q)]; n += 1
if r["fit"] != p["fit"] or abs(float(r["est_decode_tok_s"]) - p["tokensPerSec"]) > 0.15:
bad += 1; print("MISMATCH", model, q, p["id"], r["fit"], r["est_decode_tok_s"], p["fit"], p["tokensPerSec"])
print(f"checked {n} picks, {bad} outside tolerance")
|