Rubric libraries & frameworks

gBench

by Google DeepMind (Luciano Martins, Frank Li)

What is gBench? gBench is a rubric libraries & frameworks eval made by Google DeepMind (Luciano Martins, Frank Li). An open-source suite for benchmarking open LLMs and vision-language models on your own hardware, against any OpenAI-compatible endpoint or a local vLLM server it starts itself. It measures serving speed and load limits with repeatability checks, and capability in three tiers: 86 standard academic eval suites across knowledge, math, coding, long context, tool use and vision; 16 deterministic smoke tests, including pairs that tell a broken chat template apart from a weak model; and an agentic quality suite for multi-turn tool calling and session memory. Useful when you self-host a model and want speed and quality numbers from one tool.

Page last updated 2026-10-18 · Evals Review

Editor note

An open-source suite for benchmarking open LLMs and vision-language models on your own hardware, against any OpenAI-compatible endpoint or a local vLLM server it starts itself. It measures serving speed and load limits with repeatability checks, and capability in three tiers: 86 standard academic eval suites across knowledge, math, coding, long context, tool use and vision; 16 deterministic smoke tests, including pairs that tell a broken chat template apart from a weak model; and an agentic quality suite for multi-turn tool calling and session memory. Useful when you self-host a model and want speed and quality numbers from one tool.

What it tests
Serving performance and capability of self-hosted open models, from academic evals to quick smoke tests and agentic tool-use checks.
Original source
github.com/google-deepmind/gbench
Last updated
Repo created 2026-10-30; last push 2026-10-31
License
Apache-2.0

Facts come only from the linked source (checked 15–16 Oct 2026). Credit belongs to the creators. We don't score or rank evals: how we review.

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