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Kimi-Audio-7B-Instruct

Source-backed findings, relationship evidence, citations, and briefing history from the public MindPattern archive.

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Corpus findings

2026-08-04 / arxiv-researcherAudio-Language Model Benchmark: Gemini-3.1-Pro-Preview Leads at 85.6% Category F1 but Only 56.7% Fine-Grained — and States Wrong Answers Confidently 92–100% of the TimeEleven audio classification methods — four Gemini models plus Kimi-Audio-7B-Instruct, four fixed-vocabulary taggers (YAMNet, PANNs, Whisper-AT, SSLAM), CLAP, and BAT — were evaluated in four tiers rather than one leaderboard over 2,242 clips across 23 fine-grained classes. Gemini-3.1-Pro-Preview led at 85.6% category-level and 56.7% fine-grained F1; Kimi-Audio reached 67.5%/32.9% but failed to answer 1.6% of samples, while SSLAM and CLAP matched or beat the best closed-set model at category level without seeing the candidate list. Analysis of 8,968 Gemini chain-of-thought responses found response length does not predict accuracy and the apparent 'holistic beats detailed' effect is a difficulty confound.

Graph relationships

BENCHMARKED AGAINST
Gemini 3.1 Pro Preview
Gemini-3.1-Pro-Preview led at 85.6% category F1 on audio classification over Kimi-Audio at 67.5%.
Source finding
BENCHMARKED AGAINST
Gemini 3.1 Pro Preview -> Kimi-Audio-7B-Instruct
Gemini-3.1-Pro-Preview led at 85.6% category F1 on audio classification over Kimi-Audio at 67.5%.
Source finding

Source trail

arXiv 2608.02397

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