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Qwen3-Embedding-8B

by Qwen

Embedding model for semantic search, retrieval, clustering, and ranking pipelines

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Qwen3-Embedding-8B

Added 13 July 2026

#qwen

Overview

Embedding model for semantic search, retrieval, clustering, and ranking pipelines

Best for

Best for
Multilingual text retrieval

How to use / API access

Call via other with model id `Qwen/Qwen3-Embedding-8B`.

  • other · Qwen/Qwen3-Embedding-8B

OpenRouter id: qwen/qwen3-embedding-8b

Notes

Qwen3-Embedding-8B is listed in the EDNA Models directory, sourced from models.dev.

Pros

  • Embedding a multilingual collection with task instructions
  • text input; embeddings output on the listed OpenRouter route

Cons

  • Treating an embedding model as a chat generator
  • Assuming multilingual benchmark coverage proves domain recall
  • Base text-token rates exclude other modalities, tools, caching, retries and any hosting-specific charges. Check actual usage before comparing cost per successful task.
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USAGE / OPENROUTER

How much Qwen3-Embedding-8B is used

Tokens processed through OpenRouter each day. It shows what developers actually run, not every company's private traffic.

Tokens, last 7 days
190B ▲5.4%
Requests, last 7 days
61.9M
Tool calls, last 7 days
—
025B50B19 Sept: 18.7B tokens, 7.2M requests20 Sept: 22.3B tokens, 7.4M requests21 Sept: 26.5B tokens, 9.5M requests22 Sept: 26.7B tokens, 9.7M requests23 Sept: 25.2B tokens, 8.9M requests24 Sept: 24.7B tokens, 8.6M requests25 Sept: 28B tokens, 8.3M requests26 Sept: 29.1B tokens, 7.8M requests27 Sept: 14.2B tokens, 5.6M requests28 Sept: 35.2B tokens, 7M requests29 Sept: 39.3B tokens, 6.6M requests30 Sept: 38.6B tokens, 7M requests1 Oct: 30.2B tokens, 6.9M requests2 Oct: 32.6B tokens, 6.4M requests3 Oct: 21B tokens, 5.4M requests4 Oct: 23.8B tokens, 5.3M requests5 Oct: 27.1B tokens, 7M requests6 Oct: 26.8B tokens, 7.6M requests7 Oct: 28.6B tokens, 8.6M requests8 Oct: 29.6B tokens, 8.5M requests9 Oct: 21.9B tokens, 7.4M requests10 Oct: 22.3B tokens, 7.5M requests11 Oct: 24B tokens, 7.3M requests12 Oct: 22.5B tokens, 8.8M requests13 Oct: 27B tokens, 8M requests14 Oct: 27.2B tokens, 8.6M requests15 Oct: 28.7B tokens, 8.7M requests16 Oct: 32.2B tokens, 11.4M requests17 Oct: 28.6B tokens, 8.2M requests18 Oct: 23.9B tokens, 8M requests19 Sept3 Oct17 Oct18 OctSee where it ranks on the leaderboard →

MODEL FIELD GUIDE / SOURCE EVIDENCE

What you can do with Qwen3-Embedding-8B.

Specifications reviewed; no EDNA task evaluation has been run. Sources checked 2026-10-20. Hosting routes and app features can differ.

DeveloperAlibaba Qwen
Exact model identifierqwen/qwen3-embedding-8b
Inputtext
Outputembeddings
Tool calling
Not established
Structured output
Not established
Reasoning controls
Not established
Availability
available
Price basis
token
Licence verification
Check the developer licence; the model name is insufficient

Base text-token rates exclude other modalities, tools, caching, retries and any hosting-specific charges. Check actual usage before comparing cost per successful task.

Consider it for

  • Embedding a multilingual collection with task instructions
  • Testing query/document representations for semantic search

Watch for

  • Treating an embedding model as a chat generator
  • Assuming multilingual benchmark coverage proves domain recall

PRACTICAL EXERCISE / NOT RUN BY ENTERPRISE DNA

Try the model on a small, checkable task.

Encode an English query about annual leave and three documents: a Spanish leave policy, an English cafeteria menu and an English leave policy. Use the model-card retrieval instruction and rank results.

Check the result: Verify finite equal-dimension vectors and whether both leave policies rank above the menu.

Compare another approach

google gemini embedding 2 ↗openai text embedding 3 large ↗
Inspect the sources and their scope
provider source ↗

Developer documentation for model family or task. OpenRouter route-specific properties remain catalogue claims; EDNA has not executed a task evaluation.

Checked 2026-10-19
catalogue source ↗

qwen/qwen3-embedding-8b: listed route capabilities, availability and prices; provider endpoints can differ.

Checked 2026-10-20
How to evaluate a model for your work →

FROM SPECIFICATIONS TO YOUR WORK

Is this the right model for your job?

Start with a realistic sample. These workflows match the model’s listed capabilities, not a verified result on your task.

Understand the capabilitiesRead the model guide ↗

Check the source

Price date: 2026-10-20. Prices are USD API token rates. Your app subscription, uploads, browsing and tools are separate.

Model source & availability ↗

Understand the evidence

Listed capabilities and third-party benchmark scores do not establish Enterprise DNA task-test results. Validate accuracy and total cost on your own sample.

Compare this model with alternatives →