Benchmark Almanac

Golden3 speech summarization (Microsoft)

Only in system cards

Models summarize 108 recorded meetings of about 6 minutes each from 1071 instructions. GPT-4 rates overall quality from 1 to 7.

In-house Microsoft evaluation. The tasks are not public.

Made by
Microsoft
Released
March 2025
Kind
Audio understanding and voice
Level
Everyday
Scored
Graded by a model
Answers
Open-ended
Tasks
Kept private
Last in a system card
March 2025
Last model added
March 2025
1
Model scored in lab cards
1
System card reports it, from 1 lab

Phi-4-multimodal leads with 6.28

Best score per model as labs report them in their own cards. Labs pick their own settings, so these compare less cleanly than independent runs.

  1. 1 Phi-4-multimodal 6.28

Source: Labs’ model cards

#ModelScoreSettingDateSource
1 Phi-4-multimodal 6.28 Mar 2025 Lab model card

Scores over time

All the scores we have, one dot each, so a model tested at several settings appears more than once.

Reported by the lab in its model card
6.28 2025 6.28 2025

Source: Labs’ model cards

Labs report it only in system cards

We read the headline results of 522 launch posts from 52 labs, and none of them list this benchmark. Some system cards do, below.

One system card reports it

Besides launch posts, we read the system cards, model cards and technical reports labs publish with a release. They report far more, including safety and frontier-risk tests.

DateDocumentScoreAs the document writes itSection
Mar 3, 2025 Phi-4-multimodal technical report 6.28 Golden3 speech summarization, GPT-4 score 1 to 7 (Table 3). AMI 6.29 Capabilities

More in Audio and video

All 232 in Audio and video
  • Video-MMMU In use 300 expert-level lecture videos with questions testing perception, comprehension and adaptation of knowledge. Accuracy. Qwen 3.8 Max 88.7%
  • LVBench In use Hours-long video understanding with multiple-choice questions on reasoning, grounding and summarization. Gemini 4 Argon 91.7%
  • MMVU In use 3,000 expert-annotated questions on videos across 27 disciplines. Multiple-choice and open-ended accuracy. Qwen 3.8 Max 82.4%
  • MLVU In use Multi-task long video understanding (minutes to hours) with multiple-choice and generation tasks. Accuracy. Qwen 3.8 Max 90.8%
  • FLEURS In use Models transcribe read speech in 102 languages built from FLoRes-101 sentences. Model cards usually report word error rate, so lower scores are better. Phi-4-multimodal 4.00%
  • VoiceBench In use Spoken instructions with speaker, environment and content variation. Voice assistant responses scored by GPT judge or rules. Qwen3.5-Omni-Plus 93.1%