University of Kwazulu-Natal

Llm Leaderboard Stack Ai Com

Bonisiwe Shabane
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llm leaderboard stack ai com

A comprehensive list of the best LLMs in the world, ranked by their performance, price, and features, updated daily. Comprehensive testing across 57 subjects including mathematics, history, law, and medicine to evaluate LLM knowledge breadth. Graduate-level expert knowledge evaluation designed to test advanced reasoning in specialized domains. Software engineering tests including code generation, debugging, and algorithm design to measure programming capabilities. Extended version of HumanEval with more complex programming challenges across multiple languages to test code quality. Helping leaders make confident, well-informed decisions with clear benchmarks across different LLMs.

Trusted, independent rankings of large language models across performance, red teaming, jailbreaking safety, and real-world usability. This LLM leaderboard displays the latest public benchmark performance for SOTA model versions released after April 2024. The data comes from model providers as well as independently run evaluations by Vellum or the open-source community. We feature results from non-saturated benchmarks, excluding outdated benchmarks (e.g. MMLU). If you want to use these models in your agents, try Vellum.

Leaderboards have become one of the main ways to measure and compare large language models (LLMs). They help researchers, enterprises, and regulators understand how different models perform across tasks such as reasoning, coding, compliance, and multilingual capabilities. This guide reviews the most important leaderboards of 2025 and the specialized ones that continue to shape model evaluation. The Vellum leaderboard tracks the newest models released after April 2024. It compares reasoning, context length, cost, and accuracy on cutting-edge benchmarks like GPQA Diamond and AIME. Vellum’s open-source leaderboard highlights top-performing community models, with updated scores for reasoning and problem-solving.

LLM-Stats updates daily, showing speed, context window, pricing, and performance for models like GPT-5, Grok-4, and Gemini 2.5 Pro. Comparison and ranking the performance of over 30 AI models (LLMs) across key metrics including quality, price, performance and speed (output speed - tokens per second & latency - TTFT), context window & others. For more details including relating to our methodology, see our FAQs. ❖ This leaderboard is based on the following benchmarks. Chatbot Arena - a crowdsourced, randomized battle platform for large language models (LLMs). We use 6M+ user votes to compute Elo ratings.

AAII - Artificial Analysis Intelligence Index v3 aggregating 10 challenging evaluations. ARC-AGI - Artificial General Intelligence benchmark v2 to measure fluid intelligence. ❖ SWE-bench is a benchmark for evaluating large language models on real world software issues collected from GitHub. Given a codebase and an issue, a language model is tasked with generating a patch that resolves the described problem. SWE-bench Verified is a human-validated subset that more reliably evaluates AI models’ ability to solve issues. International Olympiad in Informatics (IOI) competition features standardized and automated grading.

❖ Text-to-SQL (or Text2SQL), as the name implies, is to convert text into SQL. A more academic definition is to convert natural language problems in the database field into structured query languages ​​that can be executed in relational databases. Therefore, Text-to-SQL can also be abbreviated as NL2SQL. Input: natural language questions, such as Query the relevant information of the table t_user, and the results are sorted in descending order by id. Output: SQL, such as SELECT * FROM t_user ORDER BY id DESC.

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Trusted, independent rankings of large language models across performance, red teaming, jailbreaking safety, and real-world usability. This LLM leaderboard displays the latest public benchmark performance for SOTA model versions released after April 2024. The data comes from model providers as well as independently run evaluations by Vellum or the open-source community. We feature results from non...

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Leaderboards have become one of the main ways to measure and compare large language models (LLMs). They help researchers, enterprises, and regulators understand how different models perform across tasks such as reasoning, coding, compliance, and multilingual capabilities. This guide reviews the most important leaderboards of 2025 and the specialized ones that continue to shape model evaluation. Th...

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LLM-Stats updates daily, showing speed, context window, pricing, and performance for models like GPT-5, Grok-4, and Gemini 2.5 Pro. Comparison and ranking the performance of over 30 AI models (LLMs) across key metrics including quality, price, performance and speed (output speed - tokens per second & latency - TTFT), context window & others. For more details including relating to our methodology, ...

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