更新日志

We’ve partnered with Google DeepMind to launch their Multimodal Knowledge Agent (MKA) evaluation, a new benchmark for agentic knowledge work over complex visual files

We are launching the Artificial Analysis Endpoint Accuracy Index v1.1, a minor version upgrade alongside new coverage for GLM-5.3 Flash and Muse Spark Open.

Meta's newest model Muse Ember scores 36 on the Artificial Analysis Intelligence Index, matching Claude Haiku 5.5 (max) at a third of the Cost per Task

Introducing the Artificial Analysis Decision Index v2: a new proprietary evaluation, updated benchmarks, and a headline metric that rewards model calibration

Independent VIALS-AA results, interactive agent traces, and an analysis of how models inspect scientific images.

Thinking Machines has released Inkling 2 Small, scoring 31 on the Artificial Analysis Intelligence Index - their plan to release its weights would make it the highest-scoring open weights model developed outside China based on current rankings

Nanbeige has released Nanbeige4.3-33B, an open weights model matching Qwen3.8 27B (xhigh) at 20 on the Artificial Analysis Intelligence Index v5 with stronger terminal use but weaker knowledge

Upgraded AA-LCR-25 to AA-LCR v1.1 and increased repeats from 10 to 25, tightening confidence intervals. Expanded coverage to six open weights models with GLM-5.3 Flash and Muse Spark Open.

Time per Task is the new headline for comparing models. Output Speed now covers the whole request, including the wait for the first token, and averages single-request and multi-turn agentic workloads. Token counts come from each provider's API. Failures on the endpoint's side count against it, and every endpoint shows an Endpoint Error Rate.

Incorporated grading robustness improvements from the CritPt authors and regraded all models on CritPt v2.