New Header-Only C++ Benchmark Tool for Predictive Models on Raw Binary Streams

A new header-only C++ benchmarking tool called AGITB has been released for evaluating predictive models on raw binary streams. This lightweight framework could be particularly useful for developers working on local LLM inference optimization, allowing them to benchmark different quantization schemes and model architectures directly on binary data.

The tool's header-only design makes it easy to integrate into existing C++ inference frameworks like llama.cpp or GGML-based projects. For local LLM practitioners, this could provide valuable insights into model performance characteristics before deployment, especially when working with custom quantized models or experimental inference optimizations.

You can find the project and documentation on GitHub, where the maintainer has provided examples and integration guidelines for various use cases.

Source: Hacker News · Relevance: 6/10