Head to head
Kev 4B scores 76.8 and d1-ultra 82.9 on the System One Index. Kev 4B is more accurate on 1 of 16 text datasets, d1-ultra on 14, and 1 are tied. Same cases, same request, same scorer.
| Kev 4B | d1-ultra | |
|---|---|---|
| System One Index | 76.8 | 82.9 |
| English | 78.3 | 81.7 |
| Arabic | 74.8 | 84.2 |
| Vision Index | – | 85.6 |
| Calibration error | 5.1% | 1.0% |
| Median latency | 552 ms | 168 ms |
| Cost per 1,000 calls | $0.010 | $0.010 |
| Kev 4B | d1-ultra | |
|---|---|---|
| AG News English | 90.5 | 91.0 |
| SST-2 English | 92.5 | 95.5 |
| SST-5 English | 52.0 | 61.5 |
| DAIR Emotion English | 54.5 | 63.0 |
| Banking77 English | 88.0 | 83.5 |
| BoolQ English | 91.5 | 91.5 |
| XNLI English English | 90.7 | 92.7 |
| Typed decisions English | 66.3 | 75.0 |
| XNLI French French | 79.3 | 83.3 |
| XNLI Arabic Arabic | 72.7 | 76.0 |
| MASSIVE scenario Arabic | 57.0 | 76.0 |
| MASSIVE intent Arabic | 76.5 | 87.0 |
| OSACT4 offensive Arabic | 88.5 | 94.5 |
| Tweet sentiment Arabic | 63.0 | 76.0 |
| MIRACL rerank Arabic | 79.5 | 89.0 |
| MIRACL pairwise Arabic | 86.5 | 91.0 |
| Kev 4B | d1-ultra | |
|---|---|---|
| SST-2, as an image | – | 97.0 |
| Arabic sentiment, as an image | – | 62.5 |
| Oxford-IIIT Pet | – | 87.5 |
| VQAv2 yes/no | – | 89.5 |
| CountBench | – | 91.5 |
Model pages: Kev 4B · d1-ultra. Latency for API models is the median per call through OpenRouter, timed from a cloud server with 8 calls in flight.