As large language models (LLMs) gain momentum worldwide, there’s a growing need for reliable ways to measure their performance. Benchmarks that evaluate LLM outputs allow developers to track ...

Artificial intelligence has traditionally advanced through automatic accuracy tests in tasks meant to approximate human knowledge. Carefully crafted benchmark tests such as The General Language ...

As large language models (LLMs) continue to improve at coding, the benchmarks used to evaluate their performance are steadily becoming less useful. That's because though many LLMs have similar high ...

This study introduces MathEval, a comprehensive benchmarking framework designed to systematically evaluate the mathematical reasoning capabilities of large language models (LLMs). Addressing key ...

As new large language models, or LLMs, are rapidly developed and deployed, existing methods for evaluating their safety and discovering potential vulnerabilities quickly become outdated. To identify ...

Numbers go up, AI gets better.

For Android app developers relying on AI to code, picking the right model can be tricky. Not all models are built the same, and many are not specifically trained for Android development workflows. To ...

LMArena, a popular benchmark for large language models, has been accused of giving preferential treatment to AIs made by big tech firms, potentially enabling them to game their results. When you ...

The rivalry between Qwen 3.5 and Sonnet 4.5 highlights the shifting priorities in large language model development. Qwen 3.5, ...

SINGAPORE--(BUSINESS WIRE)--Z.ai released GLM-4.7 ahead of Christmas, marking the latest iteration of its GLM large language model family. As open-source models move beyond chat-based applications and ...