VentureBeat

Train-to-Test scaling explained: How to optimize your end-to-end AI compute budget for inference

The standard guidelines for building large language models (LLMs) optimize only for training costs and ignore inference costs. This poses a challenge for real-world applications that use ...
SiliconANGLE

MLCommons releases results of its latest MLPerf AI inference benchmark test

MLCommons today released the latest results of its MLPerf Inference benchmark test, which compares the speed of artificial intelligence systems from different hardware makers. MLCommons is an industry ...
VentureBeat

Hugging Face shows how test-time scaling helps small language models punch above their weight

In a new case study, Hugging Face researchers have demonstrated how small language models (SLMs) can be configured to outperform much larger models. Their findings show that a Llama 3 model with 3B ...
The Next Platform

We Need A Proper AI Inference Benchmark Test

Companies are spending enormous sums of money on AI systems, and we are now at a point where there are credible alternatives to Nvidia GPUs as the compute engines within these systems. Given the ...
manilatimes

MLCommons Sets Participation Record with New MLPerf Inference v6.1 Benchmark Results

Latest version of the benchmark introduces two new tests for emerging AI deployment patterns, including Agentic Inference SAN FRANCISCO, Sept. 16, 2026 (GLOBE NEWSWIRE)-- MLCommons® announced new ...