Head to head
d1-ultra scores 82.9 and d3 nano 78.0 on the System One Index. d1-ultra is more accurate on 13 of 16 text datasets, d3 nano on 3. Same cases, same request, same scorer.
| d1-ultra | d3 nano | |
|---|---|---|
| System One Index | 82.9 | 78.0 |
| English | 81.7 | 77.9 |
| Arabic | 84.2 | 76.9 |
| Vision Index | 85.6 | – |
| Calibration error | 1.0% | 7.0% |
| Median latency | 168 ms | – |
| Cost per 1,000 calls | $0.010 | – |
| d1-ultra | d3 nano | |
|---|---|---|
| AG News English | 91.0 | 88.0 |
| SST-2 English | 95.5 | 89.5 |
| SST-5 English | 61.5 | 55.5 |
| DAIR Emotion English | 63.0 | 59.5 |
| Banking77 English | 83.5 | 93.0 |
| BoolQ English | 91.5 | 88.0 |
| XNLI English English | 92.7 | 87.3 |
| Typed decisions English | 75.0 | 62.6 |
| XNLI French French | 83.3 | 86.0 |
| XNLI Arabic Arabic | 76.0 | 82.0 |
| MASSIVE scenario Arabic | 76.0 | 61.5 |
| MASSIVE intent Arabic | 87.0 | 81.0 |
| OSACT4 offensive Arabic | 94.5 | 79.0 |
| Tweet sentiment Arabic | 76.0 | 71.0 |
| MIRACL rerank Arabic | 89.0 | 77.5 |
| MIRACL pairwise Arabic | 91.0 | 86.5 |
| d1-ultra | d3 nano | |
|---|---|---|
| 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: d1-ultra · d3 nano. Latency for API models is the median per call through OpenRouter, timed from a cloud server with 8 calls in flight.