AI EVALUATION, IN CONTEXT.BY EQUALITY MACHINE

LLM Stats

Wild Bench

WildBench is an automated evaluation framework that benchmarks large language models using 1,024 challenging, real-world tasks selected from over one million human-chatbot conversation logs. It introduces two evaluation metrics (WB-Reward and WB-Score) that achieve high correlation with human preferences and uses task-specific checklists for systematic evaluation.

Evaluation context and evidence

Source
LLM Stats
Publisher
Not recorded
Benchmark release
Not recorded
Collected
2026-08-17
Modality
text

These are source-reported observations, not independent reruns by this site. Check the task version, evaluation protocol, unit and reporting date before comparing models. Results from different setups are not a universal ranking.

Original sources

Reported results 8

Shown in source observation order, not ranked. Dates retain the precision provided by the source.

ModelValueUnitProtocolReported date and basisSource
MiniStral 3 (14B Instruct 2512)0.685Not recordedNot recorded2025-12-04 · model_announcementLLM Stats
Mistral Large 30.685Not recordedNot recorded2025-09-01 · model_announcementLLM Stats
Ministral 3 (8B Instruct 2512)0.668Not recordedNot recorded2025-12-04 · model_announcementLLM Stats
Mistral Small 3.2 24B Instruct0.6533Not recordedNot recorded2025-06-20 · model_announcementLLM Stats
Ministral 3 (3B Instruct 2512)0.568Not recordedNot recorded2025-12-04 · model_announcementLLM Stats
Mistral Small 3 24B Instruct0.522Not recordedNot recorded2025-01-30 · model_announcementLLM Stats
Jamba 1.5 Large0.485Not recordedNot recorded2024-08-22 · model_announcementLLM Stats
Jamba 1.5 Mini0.424Not recordedNot recorded2024-08-22 · model_announcementLLM Stats