Rankings

Evaluate AI systems on open-ended investment research.

Compare vision models on detection, counting, identification, OCR, and visual reasoning.

Evaluation of emotional intelligence in real multi-turn human-AI conversations.

A benchmark of coding models finding and fixing hidden bugs in production codebases.

Evaluation of agents performing stateful tool-use and multi-app workflows.

Question answering over document images, combining reading with document-layout understanding.

Grounded question answering about publicly traded companies using financial documents.

A collaborative collection of tasks for evaluating legal reasoning in language models.

Evaluate models on practical scientific reasoning and life-science research work.

An informal comparison of language models asked to draw a pelican riding a bicycle using SVG code.

Track AI models making forecasts through simulated prediction-market trades.

Evaluate research-level mathematical reasoning on expert-created problems.

Evaluate coding agents on resolving real software repository issues.

A catalog of evaluations for agents, professional work, reasoning, and writing.

Test multi-step numerical reasoning over financial reports.

Test numerical reasoning across conversations about financial reports.

Evaluate financial language models across document analysis, forecasting, and decisions.

Compare language models across financial questions and banking intents.

Evaluate agents researching public-company filings and financial analysis.

Test agents on extended finance assignments with realistic files and deliverables.

Test whether agents can reason through professional spreadsheets.

Evaluate strategic reasoning through competitive economic games.

Evaluate model responses to realistic health conversations with physician-written rubrics.

Test medical knowledge and reasoning using professional medical-board exam questions.

Compare models on medical entrance-exam questions across subjects and healthcare topics.

Answer biomedical research questions using evidence from corresponding PubMed abstracts.

Evaluate agents completing clinical tasks in a virtual electronic-health-record environment.

Evaluate tool-using medical agents through simulated patient encounters and multimodal clinical evidence.

Compare language models across clinical support, documentation, patient communication, research, and administration.

Test agents on extended healthcare assignments with brief handoffs and complex supporting materials.

Evaluate how precisely AI retrieves evidence from legal documents.

Compare language models on legal judgments, legislation, and contracts.

Evaluate AI on professional deliverables across major industries.

Compare customer-service agents handling retail, travel, and telecom requests.

Test agents on cybersecurity challenges in controlled environments.

Test whether tool-using agents complete tasks despite prompt-injection attacks.

Compare agents building machine-learning solutions for data-science competitions.

Compare computer-use agents on extended professional tasks.

Evaluate assistants answering questions that require research, tools, and multiple kinds of evidence.

Compare multimodal models on college-level questions across disciplines.

Test advanced scientific reasoning with expert-written questions.

Evaluate broad academic and professional knowledge across 57 subjects.

Test multi-step arithmetic reasoning through grade-school word problems.

Evaluate whether generated Python functions pass their tests.

Compare AI writing through judgments from professional writers.

Evaluate agents that turn scientific data and instructions into working analysis programs.

Assess literature, data, and protocol reasoning used in biology research.

Test code for scientific calculations, numerical methods, and simulations.

Compare agents completing difficult tasks in a terminal environment.

Evaluate freelance software fixes and choices between implementation proposals.

Evaluate whether generated CAD designs can be edited, assembled, and checked mechanically.

Measure security agents against known web-application vulnerabilities in isolated test environments.

Test whether an agent can reproduce a documented software vulnerability.

Assess interpretation of malware-analysis evidence and threat-intelligence reports.

Evaluate agents that repair security defects in native code.

Judge explanations, feedback, and hints tailored to a learner.

Assess how tutors respond to student mistakes and confusion in mathematics.

Test agents that search for and select products matching a shopper’s requirements.

Evaluate comparison shopping across stores, including compatible products and checkout.

Test visually guided web tasks, including product selection and shopping actions.

Evaluate writing against requirements specific to each assignment.

Check whether models can sustain useful writing at a requested length.

Compare short creative writing and inspect the generated samples.

Compare embedding models for search, classification, clustering, and related tasks.

Evaluate how well embedding models find relevant documents on unseen retrieval tasks.

Compare speech-to-text models on transcription accuracy and processing speed.

Evaluate Python programs that combine libraries and follow complex instructions.

Find model and agent evaluations published by research teams and the Kaggle community.

Compare AI models playing strategic games against one another.

Compare coding models on dated contest problems and code-related reasoning tasks.

Evaluate whether models use tools correctly across calls, conversations, search, and memory.

Evaluate agents querying and transforming data in complex enterprise databases.

Recreate a webpage in HTML and CSS from a screenshot.

Compare models writing and editing code across six programming languages.

Test everyday reasoning, social understanding, and resistance to misleading wording.

Infer unfamiliar visual rules from examples and apply them to new grids.

Test whether assistants remember, update, and reason about information across conversations.

Evaluate generated videos for subject consistency, motion, visual quality, and prompt alignment.

Test challenging academic knowledge and reasoning with harder multiple-choice questions.

Evaluate difficult academic questions across mathematics, science, and the humanities.

Evaluate reading text in images, answering document questions, and extracting key information.

Extract complete, structured records and supporting evidence from enterprise documents.

Evaluate AI agents creating motion graphics through code that renders into video.

Compare factual accuracy in image questions, world knowledge, search, and document-grounded responses.

Compare how much code coding agents add while solving the same tasks.

Compare AI-designed product screens with corresponding real product designs.

Test how accurately and completely agents research entities and assemble sourced answers.

Compare search APIs on scholarly, news, financial, legal, and obscure-entity queries.

Evaluate summarization, extraction, correction, and dictation from transcripts.

Test whether agents recover interrupted wet-lab experiments and protect time-sensitive samples.

Compare agents keeping research, spreadsheets, an app, and recommendations consistent as requirements change.

Compare machine-learning methods for biomedical tables with many variables and limited samples.

Test whether coding agents preserve working behavior and code quality as requirements evolve.

Evaluate the path from an application specification to a tested cloud deployment.

Evaluate agents completing research workflows contributed by scientists.

Evaluate ingredient substitution, pairing, and constrained culinary choices with executable scoring.

Test planning and tool use by having coding agents play RuneScape.

Compare code-review agents on valid findings, missed issues, and review noise.

Test whether language models write correct GPU kernels that outperform reference implementations.

Compare predictive machine-learning methods on curated tabular datasets.

Compare language models coaching opposing Blood Bowl teams.

Test recognition and reading of ancient Egyptian hieratic handwriting.

Test whether coding agents can discover and repair bugs without being told where to look.

Compare playable Pac-Man games generated from a single short prompt.

Compare raw language models reviewing the same real pull requests.

Compare generated motion graphics, rendering success, cost and time.

Test whether coding agents can reconstruct dynamic scenes from video.

Evaluate retrieval over varied company documentation and knowledge.

Compare computer-use agents on task success, speed and cost.

Test whether agents can select the next experiment from real wet-lab records.

Evaluate agents diagnosing and operating real AWS infrastructure.

Track accepted AI-assisted solutions to formal mathematics problems in Lean.

Compare AI video generators for character consistency, action scenes, and creative work.

Compare financial research grounded in filings, calculations, and evidence.

Compare AI support for market research, startup diligence, and investment memos.

Compare AI on medical questions, evidence review, and clinical documents.

Compare reading accuracy and structured extraction from scans, tables, and difficult layouts.

Compare practical coding work through working changes, independent tests, and clear review.

Compare how faithfully AI rebuilds an editable webpage from its screenshot.