//opengauntlet
// surveyed, not benchmarked

LLM quantization tools and methods compared

Every row on the leaderboard already names a quant format, and Runtimes tells you which server can load it. Neither says how that quantized checkpoint got made, or what a builder gives up doing it. Here is every quantization tool and algorithm we could verify against a primary source, on the axes that decide a project — calibration cost, bit-width, accuracy retention, and which hardware runs the result fast.

Surveyed, not benchmarked. Nothing on this page was measured by OpenGauntlet's judge pipeline.

How to read this section

None of this is scored by the judge pipeline. OpenGauntlet measures Conversational Language Humanlikeness in text. This section is a sourced survey of quantization tools and algorithms, not a trial. Where a claim could not be verified against a primary source, it says so rather than smoothing it over.

Serving is covered elsewhere. Runtimes' "quant specialist" engines (ExLlamaV3, AutoGPTQ, GPTQModel, and others) answer "can a server load this format." This page answers a different question — how the checkpoint gets produced, and what a builder gives up doing it. A tool that does both may appear on both pages, describing itself through each page's own questions.

Accuracy figures are mostly vendor-reported. This project does not run its own perplexity/quality benchmarks. Where a row's accuracy claim could not be independently confirmed, its evidence field says so rather than presenting a vendor number as measured fact.

//

Every tool, compared

Filter by kind, pick the columns you care about, search any field, click a heading to sort. Every row carries the one thing a buyer would otherwise find out too late.
Loading…
commercial-safe weights permissive, with a catch not usable commercially proprietary service discontinued
//

Claims this corrects

Each of these is repeated widely, and each is wrong.
//

What we couldn't establish

A comparison that hides its gaps is less useful than one that names them.