🔎 A simple, tiny and lightweight benchmarking library!
A small, fast chart for time series, lines, areas, ohlc & bars
JavaScript environment detection for browser and Node
JavaScript debug logging for browser and Node
Stats object for reporting performance statistics
Run benchmark with Jest
WebGL performance monitor that showing percentage of GPU/CPU load
Benchmark harness.
JavaScript implementations of network transports, cryptography, ciphers, PKI, message digests, and various utilities.
Require hook for automatic V8 compile cache persistence
Tiny tool to run commands for modified, staged, and committed git files.
Escape string for use in HTML
Run an AI trading agent (any LLM provider) against Crucible Bench scenarios on 0G — single-command MCP+EIP-712 benchmark CLI.
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<h1 align="center"> <img src="https://raw.githubusercontent.com/RafaelGSS/bench-node/refs/heads/main/assets/logo.svg" alt="Bench Node logo" /> Bench Node </h1>
Require hook for automatic V8 compile cache persistence
JavaScript console instrumentation for browser and Node
Timestamp getter wrapping (in order of preference) `process.hrtime.bigint()`, `performance.now()` or `Date.now()`
a low-level, lightweight protocol buffers implementation in JavaScript
benchmark tooling that loves you ❤️
node-simple-lru-cache =====================
Bindings for RE2: fast, safe alternative to backtracking regular expression engines.
JavaScript benchmarking utility
LLM benchmark toolkit for pi coding agent. Probes every available model with real streaming API calls and ranks by latency, cost, and output quality. Provides curated model chain and blacklist for smart model selection in pi-recap and other extensions.
CLI tool for parsing, validating, and orchestrating AGM (Agent Graph Memory) files
Core library for parsing, validating, loading, and rendering AGM (Agent Graph Memory) files
Mock OpenAI backend for benchmarking crabllm
LLM Bench is a Ruby gem that allows you to benchmark and compare the performance of different Large Language Model providers and APIs. It supports both OpenAI and Anthropic-compatible API formats, provides parallel execution, and includes continuous tracking capabilities with CSV export.
ruby-skill-bench orchestrates evaluation runs of AI coding agents inside isolated git sandboxes, then scores the results using deterministic and LLM-powered judges.
No description provided.
No description provided.