benchmark

A pure C runtime for Gemma 4 E2B CPU inference, with export, benchmarking, and numerical validation tools included.

ReactBench is a benchmark for evaluating coding agents on realistic React work, with published scores, cost comparisons, and example tasks focused on production-grade frontend issues.

An open robot football league where frontier AI models and open-source club code manage simulated Unitree G1 humanoids in daily matches, with live streams, match logs, and a public engine for teams to join.

Open-source causal-graph memory for AI agents with MCP support, scoring, active forgetting, and benchmark results published in the repo.

An open benchmark and leaderboard for AI CAD agents, with 308 prompts across 20 categories and layered scoring for geometry, engineering, manufacturability, and cognition.

Open-source repository for a NanoGPT training speedrun, focused on getting a 124M model to target loss on 8x H100 GPUs in under 90 seconds. The README includes run commands, Docker instructions, and a detailed list of model and systems optimizations.

A visual benchmark that asks AI coding agents to generate a single-file Three.js animation of a banana plant’s full life cycle, then compares the live results side by side.

Open-source harness for measuring how consistently hosted LLM APIs return the same output across repeated runs and over time, with raw transcripts, scoring, and a static leaderboard generator.

Open-source benchmark that measures which developer tools LLMs recommend when asked to build real web apps. It runs fixed prompts against a panel of models, parses the tool recommendations, and publishes rankings and head-to-head comparisons.

Public benchmark for comparing agent memory systems, with separate textual and coding tracks, submission flow, documentation, and API guidance.

An open-source benchmark for testing whether LLMs can follow long arithmetic derivations without using tools. It compares models on recall-proof inputs, logs digit accuracy, and reports results across multiple endpoints and model families.

DeepSWE is a benchmark for measuring frontier coding agents on original, long-horizon software engineering tasks. The page shows a leaderboard, methodology overview, task examples, and a full blog explaining the benchmark design and results.

A GitHub repository that publishes a week of controlled runs comparing seven Google models on the same software task, with transcripts, telemetry, screenshots, and scored benchmark artifacts.

A black-box benchmark report on how AI-generated tests detect functional bugs in live APIs across 20 scenarios and 7 systems.

A GitHub repo section documenting a benchmark for Vestige, a local-first Rust MCP memory layer for multi-agent coding fleets. The page explains the benchmark setup, what is being measured, how to reproduce the main claim, and where to find transcripts, evidence, and harness code.

A workbench report comparing MiniMax M3 and GLM 5.2 on autonomous coding tasks, with scored results, latency and cost data, task-type breakdowns, and examples of where each model performed better.

A showcase of 27 explorable Three.js worlds built autonomously by 9 coding models from the same brief.

A Topos case study showing how a guided refactor of a synthetic healthcare claims engine reduced token usage, wall time, and estimated cost for later Gemini feature sessions.

Public evaluation code for an Agent Memory Leaderboard, including answer-generation and scoring contracts for comparing LLM agent memory systems.

An in-depth Medium post from IronBee about how a verification loop affects AI coding agents, using Web-Bench and comparing DeepSeek with Claude Opus on a real web app task.

A playful benchmark dashboard that ranks LLMs based on one person's 10-question scoring process.