Skip to content
01

Providers + pricing

CapabilitiesProvider details
● Your own key · billed by your provider · AnyRouter fee $0
DeepInfra
deepinfra-byok
$0.01list$0list
Unavailable
OVHcloud
ovhcloud-byok
$0.12list$0list
Unavailable
● Free pool · donated keys · not available for this model — donate a key
02

Try it

POST /api/v1/embeddings
import OpenAI from "openai" const client = new OpenAI({  apiKey: process.env.ANYROUTER_API_KEY,  baseURL: "https://anyrouter.dev/api/v1",}) const resp = await client.embeddings.create({  model: "qwen/qwen3-embedding-8b",  input: "The quick brown fox jumps over the lazy dog",})console.log(resp.data[0].embedding.slice(0, 8))
Set ANYROUTER_API_KEY · edits on the demo update this code
Live demo
Cosine similarity
—
03

Uptime + latency

—recent checks · all routes

No health checks recorded for this model yet.

24h
No traffic in the last 24h.
More performance detail
Usage analytics

Loading usage…

Uptime & Health
No uptime data yet

These providers haven't been health-probed for this model yet. The router still routes around upstreams that fail live requests — uptime fills in once probe history accrues.

Qwen3 Embedding 8B

  • DeepInfra
  • OVHcloud
Embedtext → [0.12, -0.4, …]4096dimensions
Context
33K
Input
$0.01
Output
$0
TTFT
—
Uptime
—
Routes
2
04

Your access

Credits
Your own key · AnyRouter fee $0

Run Qwen3 Embedding 8B on your own key — your requests are billed by the provider. Pool callers pay AnyRouter credits.

No BYOK keys configured for this model yet.

Share a key with the pool to earn credits for every request it serves, covering your plan cost.

Free poolnot in pool yetDonate key →
Create API key for this model
Embedding vectors
Vector dimensions4,096
Max input32,768 tokens
Price$0.01 / 1M tokens
Request parameters
inputmodeldimensionsencoding_format
ArchitectureTransformer
Categoryembedding
ReleasedJun 4, 2025
Modalities
→
Capabilities
Embeddings are fixed-length vectors — compare them with cosine similarity for semantic search, RAG retrieval, clustering, and deduplication. Embed queries and documents with the same model, or the distances are meaningless.
05

About

Qwen3 8B embedding model for text embedding tasks with a 32,768 token context window.

Released 2025-06-04 · params: input · model · dimensions · encoding_format

Share cards
Qwen3 Embedding 8B share card
Qwen3 Embedding 8B
DeepInfra upstream share card
DeepInfra upstream
OVHcloud upstream share card
OVHcloud upstream
Back to models