PREVIEW · all numbers on this page are illustrative sample data, not measurements. First real soundings coming soon.

AA for local inference

Understand the AI landscape to choose the best model and hardware for your local inference

6 models5 quants6 GPUs5 engines— runs

Intelligence vs. Speed on your GPU

Local Intelligence Index (higher is better) vs. decode tokens/s (higher is better) · best engine per point ·
● filled = fits in VRAM · ○ hollow = CPU/RAM offload · size = file size · dashed = Pareto frontierillustrative data

Decode speed by GPU

Output tokens per second · higher is better ·
Missing bar = engine not supported or model does not fit with that engineillustrative data

What should I run?

Best quality that meets your speed floor · 64 GB system RAM

Soundings

All runs for the selected GPU · click a column to sort
ModelQuantEngineFile Decode t/sPrefill t/sIndexModeStatus
Status: ● verified = our run or ≥ 2 matching community runs · ● community = single submissionillustrative data
Ping

One standard run for every model × quant × engine × GPU: same prompts, contexts 512 / 8k / 32k, fixed seeds, warm-up excluded.

Echo

We record prefill and decode speed, TTFT, peak VRAM/RAM and KLD vs. BF16. Raw logs and the exact engine commit ship with every run.

Chart

Run it yourself: fathometer run <model> --engine llama.cpp then fathometer submit. Coming soon.