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 ...

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 ...

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

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 ...

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

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

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

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

Alibaba Qwen 3.5 Small models run offline on phones and laptops; 0.8B and 2B sizes, with mixed reliability on hard tasks.

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