Models/Qwen/Qwen3-Embedding-8B

Qwen3 Embedding 8B

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Qwen/Qwen3-Embedding-8B·Qwen · Apache 2.0 · updated 2026-01-22

RecommendedEmbeddingMultilingual

Overview

Top open-weight model on MTEB v2 retrieval, 4096 dimensions.

Use cases: Embedding · Multilingual

Context32,768

Max output—

Capabilities

ToolsParallel toolsStructured outputStreamReasoningCacheBatchVision

GridPort billing priceUSD / 1M tokens

UnitStandardBatch

Input tokens$0.010—

Live metricslast hour

Last hour of customer requests; each metric needs at least 20 valid samples.Samples this hour: 0 for TTFT, 0 for throughput · as of 2026-10-07 00:35 EDT

TTFT p50—

Throughput p50—

Success rate—

Routes2 · failover on

import os
from openai import OpenAI

client = OpenAI(
    base_url="https://gridport.ai/v1",
    api_key=os.environ["GRIDPORT_API_KEY"],
)
resp = client.embeddings.create(
    model="Qwen/Qwen3-Embedding-8B",  # pin a version: "Qwen/Qwen3-Embedding-8B@2026-01-22"
    input=["The quick brown fox","jumps over the lazy dog"],
)
print(len(resp.data), "vectors of", len(resp.data[0].embedding), "dimensions")

Known limits

01Prompt cache belongs to a route: a failover to the backup route starts with a cold cache.02Rate limits apply per organization, project and key, and per model where one is set; the strictest applies.03Streaming responses carry usage in the final chunk only when stream_options.include_usage is set.

Versions

VersionStatusReleasedRetires

2026-01-22defaultActive2026-01-22—