HealthBench

getbased is an open-source, local-first personal health dashboard and self-hostable web application, with a hosted version at getbased.health. It combines laboratory results, DNA data, wearable and body metrics, light exposure, lifestyle context, therapy histories, and personal notes in a browser-based workspace. Lab reports can be imported from PDFs, images, and spreadsheets or entered manually; known markers are mapped for review, then tracked with charts and context-aware ranges. The application calculates supported ratios and indices through deterministic fallbacks, including biological age when the required inputs are available, and produces Biology Scores that summarize marker patterns rather than diagnose conditions. DNA support includes consumer and clinical raw-DNA formats, curated SNP interpretation, APOE haplotypes, and mitochondrial DNA haplogroups. The dashboard also supports selected wearable connections, local Apple Health file imports, manual measurements, light and environmental tracking, and structured therapy histories. It can run without an account and stores most data in the browser by default; AI analysis, encrypted synchronization, profile sharing, external Knowledge Bases, and Agent Access are opt-in. The project can be self-hosted or used through its hosted application.

Terminal Bench 4 is a benchmark for comparing coding-model performance across tasks with different difficulty levels.

CommerceAgentBench is a benchmark developed and maintained by the Accio team at Alibaba International for evaluating whether AI agents can complete long-horizon business workflows in high-fidelity, stateful, reproducible replicas of online services. Its tasks cover browser operations, native-style command-line tools, file and spreadsheet production, API and MCP workflows, public-web research, supplier analysis, product publishing, logistics, storefront configuration, and other commerce operations. Each task runs in a fresh container and is graded by a deterministic or LLM-assisted verifier. The benchmark uses local mock services representing commerce, SaaS, messaging, document, and operational systems; runs preserve the resolved configuration, agent trajectory, verifier result, artifacts, logs, and container metadata for auditing and reproducibility. The repository describes 107 tasks spanning CLI, browser, file, and API/MCP interfaces, with text-only, browser-text-capable, and vision-required capability slices. The project was previously called RealReplicaBench.

Assistant Benchmark is a comparative evaluation of AI assistants created by David Pawlan. It gives different assistants the same real-world prompts, including tasks such as email management, travel booking, and financial administration, and compares their outcomes, follow-up questions, speed, and performance across 16 dimensions. The benchmark is based on ongoing testing of multiple assistants and examines both task execution and the degree of autonomy assistants can usefully take.

PerceptionBench is a benchmark for evaluating atomic visual perception in multimodal large language models (MLLMs). It isolates perception from reasoning and domain knowledge by defining ten atomic perceptual capabilities, including counting, depth, localization, OCR, and perception-related hallucination, based on an error taxonomy derived from failures across existing benchmarks. The released dataset contains 3,000 verified open-ended questions with short, uniquely determined answers; 1,800 are decomposed from failures in source benchmarks and 1,200 are newly authored using supplementary images. The repository provides the benchmark's code and links to its paper and dataset.