Qwen 3 Embedding 4B vs Seed1.6 Embedding 1215
MTEB multilingual v2 · Mean over tasks · multilingual (1037 languages) Embeddings assign examples to categories, group similar examples, estimate semantic similarity between pairs, classify relationships between pairs, rank relevant documents for queries, find translated sentence pairs, rerank documents according to instructions, assign multiple labels to each example, reorder candidate documents by relevance on MTEB Multilingual v2 · mean over tasks in 1037 languages including 'Auhelawa, Abau, Achi, Achinese, Achuar-Shiwiar, Adzera, Afrikaans, Agarabi; tasks receive equal weight
Qwen 3 Embedding 4B69.4
Seed1.6 Embedding 121570.3
| Benchmark | Qwen 3 Embedding 4B | Seed1.6 Embedding 1215 |
|---|---|---|
| MTEB multilingual v2 · Mean over tasks · multilingual (1037 languages) | 69.4 | 70.3 |
Specs
| Spec | Qwen 3 Embedding 4B | Seed1.6 Embedding 1215 |
|---|---|---|
| Price | !$0.02 | — |
| Context | 33K | 33K |
| Weights | Open | Closed |
| Released | Jun 2025 | Dec 2025 |
| Dimensions | 2,560 | — |
| Max input | 33K tokens | 33K tokens |
| Memory (4-bit) | 2.4 GB | — |
| Licence | Apache-2.0 | — |
| Commercial use | Allowed | — |
What breaks when you switch
Qwen 3 Embedding 4B → Seed1.6 Embedding 1215
Re-embed your whole corpus›
Vectors from different models can't be mixed.
Seed1.6 Embedding 1215 → Qwen 3 Embedding 4B
Re-embed your whole corpus›
Vectors from different models can't be mixed.