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

Alternatives to KaLM-Embedding-Gemma3-12B-2511

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

Alternatives to Qwen3-Embedding-8B

Task by task

TaskKaLM-Embedding-Gemma3-12B-2511Qwen3-Embedding-8BHigher tier
Embeddings & retrieval
Models
S72.3% on MTEB(Multilingual, v2) · LocalS70.6% on MTEB(Multilingual, v2) · LocalSame 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

BenchmarkKaLM-Embedding-Gemma3-12B-2511Qwen3-Embedding-8BSnapshot
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