I benchmarked how good LLMs are at proofreading English
Agent loop proofreading evals where HELM and LMSys are too generic.
Adversarial multi-turn benchmark for LLM debate quality, using side-swapped matchups and multi-model judging to rank models by judged debate performance.
Side-swapped debate matchups expose model weaknesses standard benchmarks miss.
LLM researchers and AI developers evaluating model capabilities
LMSys Arena · HELM · BigBench
Agent loop proofreading evals where HELM and LMSys are too generic.
Orchestrates real-time skepticism between models to catch hallucinations before you see them.
2B model beats 12B on some tasks, saving hardware costs for edge deployment.
Tracks which dev tools AI agents actually choose across thousands of prompts.
Sequential-dispatch methodology corrects 20x overestimation in prior WebGPU benchmarks.
ec2instances.info for LLMs—clean comparison table with real-time pricing and benchmarks.