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reasoning benchmark

VoiceBench Avg

VoiceBench is the first benchmark designed to provide a multi-faceted evaluation of LLM-based voice assistants, evaluating capabilities including general knowledge, instruction-following, reasoning, and safety using both synthetic and real spoken instruction data with diverse speaker characteristics and environmental conditions.

Updated Aug 11, 2026

Models1
Model coverage1
MetricScore
EvidenceB

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VoiceBench Avg Ranking

Higher score ranks better on this benchmark.

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01ACQwen2.5-Omni-7BAlibaba Cloud / Qwen Team74.1%100.0%1CAug 11, 2026

VoiceBench Avg Highlights

The leading models and scores on this benchmark.

Rank #1Qwen2.5-Omni-7B74.1%

What is VoiceBench Avg?

What VoiceBench Avg measures and how its scores work.

VoiceBench is the first benchmark designed to provide a multi-faceted evaluation of LLM-based voice assistants, evaluating capabilities including general knowledge, instruction-following, reasoning, and safety using both synthetic and real spoken instruction data with diverse speaker characteristics and environmental conditions.

Scores are shown in ratio. This benchmark is not independently verified and has an evidence level of B.

Family
VoiceBench Avg
Modality
multimodal
Primary category
reasoning
Score direction
higher
LLMBoard eligible
No
Evaluation key
voicebench-avg|llm-stats-current

Benchmark scores retain their original unit. Overall score eligibility is shown separately.

FAQ

Common questions about VoiceBench Avg.

Which model scores highest on VoiceBench Avg?

Qwen2.5-Omni-7B is currently ranked first with 74.1%.

What does VoiceBench Avg measure?

VoiceBench is the first benchmark designed to provide a multi-faceted evaluation of LLM-based voice assistants, evaluating capabilities including general knowledge, instruction-following, reasoning, and safety using both synthetic and real spoken instruction data with diverse speaker characteristics and environmental conditions.

Is a higher score better?

Yes. Higher values rank better for this benchmark.

How many models are compared?

1 model results are currently shown.

Does this benchmark affect the overall score?

No. This benchmark is shown for reference but does not contribute to the overall score.