KaLM Embedding Gemma3 12B 2511 vs Llama Embed Nemotron 8B
KaLM Embedding Gemma3 12B 251172.3
Llama Embed Nemotron 8B69.5
| Benchmark | KaLM Embedding Gemma3 12B 2511 | Llama Embed Nemotron 8B |
|---|---|---|
| MTEB multilingual v2 · Mean over tasks · multilingual (1037 languages) | 72.3 | 69.5 |
Specs
| Spec | KaLM Embedding Gemma3 12B 2511 | Llama Embed Nemotron 8B |
|---|---|---|
| Context | 33K | 33K |
| Weights | Open | Open |
| Released | Nov 2025 | Oct 2025 |
| Dimensions | 3,840 | 4,096 |
| Max input | 131K tokens | 131K tokens |
| Memory (4-bit) | 7.1 GB | 4.5 GB |
| Licence | tencent-kalm-embedding-community | https://huggingface.co/nvidia/llama-embed-nemotron-8b/blob/main/LICENSE |
| Commercial use | Restricted | Restricted |
What breaks when you switch
KaLM Embedding Gemma3 12B 2511 → Llama Embed Nemotron 8B
Re-embed your whole corpus›
Vectors from different models can't be mixed; dimensions change from 3,840 to 4,096.
Llama Embed Nemotron 8B → KaLM Embedding Gemma3 12B 2511
Re-embed your whole corpus›
Vectors from different models can't be mixed; dimensions change from 4,096 to 3,840.