Qwen3 Embedding 8B
Features 8 billion parameters with 32K token context length supporting 100+ natural and programming languages. Ranks #1 on MTEB multilingual leaderboard with 70.58 score as of June 2025. If you want to compare the best embedding models for your data, try Agentset.
Model Information
- Provider
- Qwen
- License
- Open Source
- Price per 1M tokens
- $0.050
- Dimensions
- 4096
- Release Date
- 2025-06-06
- Model Name
- qwen3-embedding-8b
- Total Evaluations
- 830
Performance Record
Embedding Models Are Just One Piece of RAG
Agentset gives you a managed RAG pipeline with the top-ranked models and best practices baked in. No infrastructure to maintain, no embeddings to manage.
Trusted by teams building production RAG applications
Performance Overview
ELO ratings by dataset
Qwen3 Embedding 8B's ELO performance varies across different benchmark datasets, showing its strengths in specific domains.
Qwen3 Embedding 8B - ELO by Dataset
Detailed Metrics
Dataset breakdown
Performance metrics across different benchmark datasets, including accuracy and latency percentiles.
business reports
Accuracy Metrics
- nDCG@5
- 0.000
- nDCG@10
- 0.000
- Recall@5
- 0.000
- Recall@10
- 0.000
Latency Distribution
- Mean
- 48ms
- P50 (Median)
- 48ms
- P90
- 48ms
DBPedia
Accuracy Metrics
- nDCG@5
- 0.806
- nDCG@10
- 0.797
- Recall@5
- 0.062
- Recall@10
- 0.123
Latency Distribution
- Mean
- 49ms
- P50 (Median)
- 49ms
- P90
- 49ms
FiQa
Accuracy Metrics
- nDCG@5
- 0.884
- nDCG@10
- 0.880
- Recall@5
- 0.736
- Recall@10
- 0.818
Latency Distribution
- Mean
- 30ms
- P50 (Median)
- 30ms
- P90
- 30ms
SciFact
Accuracy Metrics
- nDCG@5
- 0.739
- nDCG@10
- 0.744
- Recall@5
- 0.840
- Recall@10
- 0.881
Latency Distribution
- Mean
- 41ms
- P50 (Median)
- 41ms
- P90
- 41ms
MSMARCO
Accuracy Metrics
- nDCG@5
- 0.945
- nDCG@10
- 0.937
- Recall@5
- 0.123
- Recall@10
- 0.223
Latency Distribution
- Mean
- 39ms
- P50 (Median)
- 39ms
- P90
- 39ms
ARCD
Accuracy Metrics
- nDCG@5
- 0.851
- nDCG@10
- 0.857
- Recall@5
- 0.920
- Recall@10
- 0.940
Latency Distribution
- Mean
- 35ms
- P50 (Median)
- 35ms
- P90
- 35ms
Build RAG in Minutes, Not Months
Agentset gives you a complete RAG API with top-ranked embedding models and smart retrieval built in. Upload your data, call the API, and get accurate results from day one.
import { Agentset } from "agentset";
const agentset = new Agentset();
const ns = agentset.namespace("ns_1234");
const results = await ns.search(
"What is multi-head attention?"
);
for (const result of results) {
console.log(result.text);
}Compare Models
See how it stacks up
Compare Qwen3 Embedding 8B with other top embeddings to understand the differences in performance, accuracy, and latency.