Munibench
Munibench provides a flexible, callback-driven framework for running benchmarks against memory-augmented LLM systems. It is designed specifically for long-context and memory evaluation tasks, allowing researchers to easily instrument and measure how well different memory architectures perform on complex retrieval and reasoning benchmarks. The package is distributed via PyPI and is intended for use in research and development workflows.
Overview
3 featuresMunibench is a Data science & ML workbench project. It focuses on evaluating and benchmarking memory systems for large language models. Munibench is an open-source project aimed at AI researchers and developers. The project is open source (Open Source). Munibench is available on the command line.
Munibench first shipped in 2026. Among its 3 catalogued features are callback-based runner, memory system evaluation, and LLM benchmarking.
Summary written by a language model from the project’s public pages.
- Callback-based runner
- Memory system evaluation
- LLM benchmarking
Built with & integrations
Trust & compliance
Indexing history
1What PulseGate has recorded for this listing
Frequently asked questions about Munibench
- What does Munibench do?
- Munibench focuses on evaluating and benchmarking memory systems for large language models. It is catalogued under Data science & ML workbench on PulseGate.
- Who is Munibench for?
- Munibench is an open-source project built for AI researchers and developers.
- Does Munibench have a free plan?
- Yes — Munibench is open source under the Open Source license and free to use.
- What platforms does Munibench run on?
- Munibench runs on the command line.
- Is Munibench still maintained?
- Unverified. Munibench has not been re-checked since it entered the index, so there is no finding either way — and only a positive finding would say otherwise.
- How long has Munibench been around?
- Munibench first shipped in 2026.
- Is Munibench open source?
- Yes — Munibench is open source under the Open Source license.
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