Model card
SenseNova-U1-A3B-MoT.
SenseTimeLarge language model1 current SOTA
Added from Papers with Code MMLU-Pro refresh on 2026-05-19.
§ 02 · Benchmarks
Every benchmark SenseNova-U1-A3B-MoT has a recorded score for.
| # | Benchmark | Area · Task | Metric | Value | Rank | Date | Source |
|---|---|---|---|---|---|---|---|
| 01 | GenEval | Multimodal · Text-to-Image Generation | geneval-score | 0.9% | #1 | — | source ↗ |
| 02 | MMBench | Multimodal · Visual Question Answering | accuracy | 91.6% | #1 | — | source ↗ |
| 03 | MMStar | Multimodal · Image-Text-to-Text | accuracy | 80.9% | #6 | — | source ↗ |
| 04 | MMMU | Multimodal · Image-Text-to-Text | accuracy | 80.5% | #9 | — | source ↗ |
| 05 | Tau2-Bench | Agentic AI · Tool Use | accuracy | 75.4% | #10 | — | source ↗ |
| 06 | MMMU-Pro | Multimodal · Visual Question Answering | accuracy | 72.8% | #16 | — | source ↗ |
| 07 | MMLU-Pro | Reasoning · Commonsense Reasoning | accuracy | 84.0% | #35 | 2026-05-12 | source ↗ |
| 08 | MMLU-Pro | Reasoning · Commonsense Reasoning | accuracy | 84.0% | #35 | — | source ↗ |
Rank column shows this model’s position vs all other models scored on the same benchmark + metric (competitors after the slash). #1 in red means current SOTA. Sorted by rank, then newest result.
§ 03 · Strengths by area
Where SenseNova-U1-A3B-MoT actually performs.
§ 04 · Papers
1 paper with results for SenseNova-U1-A3B-MoT.
§ 06 · Sources & freshness
Where these numbers come from.
pwc-dump
7
results
paperswithcode
1
result
0 of 8 rows marked verified.