BASIS-Bench - SQA SD-QA Accent: leaderboard
Table 8 content tasks evaluate spoken-question answering and speech transcription across demographic and accent slices. These are generated content scores; the separate demographic classification and stereotyping metrics are not imported here. ASR uses the published 100 minus WER, whose lower bound is unbounded.
Metric: Accuracy (%). Source: arxiv.org. Saturation forecast: Estimated already saturated. 8 models tracked.
Top models
| # | Model | Score | Overall rank |
|---|---|---|---|
| 1 | Qwen3 Omni 30B A3B Instruct | 81.6 | #364 |
| 2 | Voxtral-Small-24B-2507 | 80.9 | #569 |
| 3 | Qwen2.5-Omni-7B | 79.1 | #608 |
No result here: #3 Claude Opus 5.5, #5 GPT-6 Astra, #7 Gemini 4 Argon.
Interactive version: theaggregate.ai/benchmark?slug=basis-bench-sqa-sd-qa-accent · How It Works · Data refreshed daily, snapshot 2026-10-16.