UK universities release TEASBench: measuring AI inference cost and performance across hardware
PontiEdoardo · x · 2026-09-01
Developed at Edinburgh, EPCC and Imperial College under ARIA's "Scaling compute" programme, TEASBench is an open benchmark suite measuring cost, accuracy, and performance of AI inference on diverse hardware. Unlike benchmarks with fixed context lengths, it doesn't constrain input/output tokens, exposing real-world hardware limits, and also reports energy and user-experience estimates. It evolves on a 6-monthly cycle — the August 2026 release covers sparse MoE and reasoning models — with NVIDIA supported first and AMD/Tenstorrent pipelines coming.
More from Infra
- DIT launches AI token exchange to route requests, claiming 30–70% cost savings — Div_pradeep · 2026-09-01
- Anthropic commits $80B to cloud capacity in a single month — kimmonismus · 2026-09-01
- ESP32 voice assistant: 8x wake-word model compression with AIMET — carrycooldude · 2026-09-01
- LITE plans VCSEL products for AI interconnects, delayed by 1-2 years — zephyr_z9 · 2026-09-01
- Xiaohongshu & NVIDIA build GR-Inference engine, doubling throughput for Beam Search — 小红书技术REDtech · 2026-09-01
- antirez shows DeepSeek v4 Flash vision running fast locally on an M5 Max; Metal/CUDA/ROCm support nearly ready — antirez · 2026-09-01