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 ...

AI development is often framed as a race among countries, companies and academic researchers. But figuring out who’s actually ...

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

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 ...

Researchers debut "Humanity’s Last Exam," a benchmark of 2,500 expert-level questions that current AI models are failing.

In updated tests published to the Humanity's Last Exam website, Gemini's 3.1 Pro model achieved 45.9 percent accuracy, with a ...

MLCommons recently launched AILuminate, the first safety test specifically designed for LLMs. The v1.0 benchmark generates safety grades for widely adopted LLMs and represents a collaborative effort ...

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

Large language models (LLMs), artificial intelligence (AI) systems that can process human language and generate texts in ...

Explore how vision-language-action models like Helix, GR00T N1, and RT-1 are enabling robots to understand instructions and act autonomously.