Llama Embed Nemotron 8B vs Seed1.6 Embedding 1215
Llama Embed Nemotron 8B69.5
Seed1.6 Embedding 121570.3
| Benchmark | Llama Embed Nemotron 8B | Seed1.6 Embedding 1215 |
|---|---|---|
| MTEB multilingual v2 · Mean over tasks · multilingual (1037 languages) | 69.5 | 70.3 |
Specs
| Spec | Llama Embed Nemotron 8B | Seed1.6 Embedding 1215 |
|---|---|---|
| Context | 33K | 33K |
| Weights | Open | Closed |
| Released | Oct 2025 | Dec 2025 |
| Dimensions | 4,096 | — |
| Max input | 131K tokens | 33K tokens |
| Memory (4-bit) | 4.5 GB | — |
| Licence | https://huggingface.co/nvidia/llama-embed-nemotron-8b/blob/main/LICENSE | — |
| Commercial use | Restricted | — |
What breaks when you switch
Llama Embed Nemotron 8B → Seed1.6 Embedding 1215
Re-embed your whole corpus›
Vectors from different models can't be mixed.
Max input: 131K tokens → 33K tokens
Seed1.6 Embedding 1215 → Llama Embed Nemotron 8B
Re-embed your whole corpus›
Vectors from different models can't be mixed.