All tasks / Comparisons
KaLM-Embedding-Gemma3-12B-2511 vs Qwen3-Embedding-8B
Compared only on public benchmark results, across the 1 task where both are listed: they share a tier in 1.
KaLM-Embedding-Gemma3-12B-2511
Tencent's open-weights 12B multilingual text embedding model built on Gemma 3.
- Vendor
- Tencent
- Weights
- Open: run it yourself
- Released
- Nov 2025
- GPU memory to run locally
- ~24 GB
- License
- Tencent KaLM Embedding Community License
- Last verified
- 19 Oct 2026
Qwen3-Embedding-8B
Alibaba's Apache-2.0 open-weights multilingual text embedding models in 0.6B, 4B and 8B sizes.
- Vendor
- Alibaba (Qwen)
- Weights
- Open: run it yourself
- Released
- Jun 2025
- GPU memory to run locally
- ~16 GB
- License
- Apache-2.0
- Last verified
- 19 Oct 2026
Task by task
| Task | KaLM-Embedding-Gemma3-12B-2511 | Qwen3-Embedding-8B | Higher tier |
|---|---|---|---|
| Embeddings & retrieval Models | S72.3% on MTEB(Multilingual, v2) · Local | S70.6% on MTEB(Multilingual, v2) · Local | Same tier |
A tier spans a range of scores, and small gaps on a leaderboard are often within its margin of error, so only a different tier counts as ahead. How we rank.
Same benchmark, both results
| Benchmark | KaLM-Embedding-Gemma3-12B-2511 | Qwen3-Embedding-8B | Snapshot |
|---|---|---|---|
| MTEB(Multilingual, v2) Mean (Task): average main score over 131 multilingual tasks (bitext mining, classification, clustering, retrieval, reranking, STS, instruction reranking), higher is better | 72.3% | 70.6% | 19 Oct 2026 |