Qwen3 Embedding 8B API
Alibaba Qwen multilingual text embeddings, 100+ languages and strong on Chinese, with a vector length you choose.
Qwen3 Embedding 8B is a text embedding model from Qwen, available on OttoPort's OpenAI-compatible API as the model ID qwen3-embedding-8b at $0.011 per 1M input tokens as of 2026-10-14.
Provider
Qwen
Price
$0.011 per 1M input tokens
Model ID
qwen3-embedding-8b
Type
text embedding model
Qwen3 Embedding 8B API pricing
What OttoPort bills for Qwen3 Embedding 8B, and what that works out to per unit. Rates are read from the same catalog the gateway meters against, and were current on 2026-10-14.
| Per 1M tokens | $0.011 | input text; the vectors are not billed |
|---|---|---|
| 10,000 passages | $0.055 | of about 500 tokens each, embedded once |
| Tokens per $1 | 90,909,090 |
No subscription and no minimum — OttoPort bills prepaid credits against usage. See the full rate card.
Call Qwen3 Embedding 8B in three lines
Send "model": "qwen3-embedding-8b" to POST https://ottoport.ai/api/v1/embeddings with an OttoPort key. No Qwen account, no waitlist, no separate SDK.
curl https://ottoport.ai/api/v1/embeddings \
-H "Authorization: Bearer $OTTOPORT_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "qwen3-embedding-8b",
"input": ["How do refunds work?", "Refunds are issued within 5 days."],
"dimensions": 1024
}'from openai import OpenAI
client = OpenAI(
api_key="op-...", # your OttoPort key
base_url="https://ottoport.ai/api/v1", # the only line that changes
)
resp = client.embeddings.create(
model="qwen3-embedding-8b",
input=["How do refunds work?", "Refunds are issued within 5 days."],
dimensions=1024,
)
vectors = [item.embedding for item in resp.data]import OpenAI from "openai";
const client = new OpenAI({
apiKey: "op-...", // your OttoPort key
baseURL: "https://ottoport.ai/api/v1", // the only line that changes
});
const resp = await client.embeddings.create({
model: "qwen3-embedding-8b",
input: ["How do refunds work?", "Refunds are issued within 5 days."],
dimensions: 1024,
});
const vectors = resp.data.map((item) => item.embedding);Before you start
- 1. Create a key at /api-keys.
- 2. Top up credits — the smallest pack is $25.
- 3. Paste the request. It returns on the same request.
Full reference at /docs, or drive it from an agent with the MCP server and CLI.
Request parameters
The body POST https://ottoport.ai/api/v1/embeddings accepts for Qwen3 Embedding 8B.
| Field | Type | Required | Notes |
|---|---|---|---|
| model | string | Yes | Always qwen3-embedding-8b for Qwen3 Embedding 8B. |
| input | string | array | Yes | One text, or an array of up to 256, each non-empty; 600,000 characters in all. One vector comes back per text, in order. Input tokens are the billed unit. |
| dimensions | integer | No | Vector length, up to 4096; default 4096. Shorter vectors are cheaper to store and search. |
| encoding_format | string | No | `float` (default) or `base64`, little-endian float32. |
Qwen3 Embedding 8B direct vs through OttoPort
Qwen3 Embedding 8B is the same model either way — what changes is how many accounts, keys, and integrations you carry to reach it.
| Qwen direct | Via OttoPort | |
|---|---|---|
| Accounts and keys | A Qwen account, plus one more for every other model you add | One OttoPort account and one key for the whole catalog |
| Request shape | Qwen's own SDK and response format | OpenAI-compatible — point baseURL at OttoPort and change the model string |
| Switching models | A new integration per provider | Replace qwen3-embedding-8b with any other model ID in the catalog |
| Billing | A separate invoice and contract per provider | Prepaid credits, no subscription, one usage ledger |
| Provider outages | Your call fails | Configured backup routes are tried in order on provider failure |
Embed queries and documents with the same model.
Batch up to 256 texts in one request.
Pick `dimensions` once and keep it.
Qwen3 Embedding 8B API questions
Cost, keys, and model IDs for Qwen3 Embedding 8B on OttoPort.
How much does the Qwen3 Embedding 8B API cost?
On OttoPort, Qwen3 Embedding 8B costs $0.011 per 1M input tokens as of 2026-10-14. For scale, 10,000 passages: $0.055. Billing is prepaid usage with no subscription and no minimum, and the current rate is always published at ottoport.ai/pricing.
How do I get a Qwen3 Embedding 8B API key?
You do not need a Qwen key. Create an OttoPort account, generate a key at ottoport.ai/api-keys, and send it as "Authorization: Bearer <key>" to POST https://ottoport.ai/api/v1/embeddings with "model": "qwen3-embedding-8b". The same key reaches every other model in the catalog.
What is the model ID for Qwen3 Embedding 8B?
The OttoPort model ID for Qwen3 Embedding 8B is qwen3-embedding-8b. Pass it as the model field on POST https://ottoport.ai/api/v1/embeddings, or list it programmatically from GET https://ottoport.ai/api/v1/models.
Can I call Qwen3 Embedding 8B with the OpenAI SDK?
Yes. Set the OpenAI SDK's base URL to https://ottoport.ai/api/v1, use an OttoPort API key, and pass qwen3-embedding-8b as the model. Embeddings follow the OpenAI embeddings shape, so existing code works after changing two lines.
How many dimensions does Qwen3 Embedding 8B return?
4,096 by default. Send dimensions to get a shorter vector, up to 4,096; it is billed the same, by input tokens. Embed every text you compare with the same model and the same dimensions.
Do I need a Qwen account to use Qwen3 Embedding 8B?
No. OttoPort connects to Qwen on your behalf, so one OttoPort account covers Qwen3 Embedding 8B and every other model in the catalog — no per-provider contracts, keys, or invoices.
Other text embedding models on the same API
Same endpoint, same key — swapping model is a one-string change from qwen3-embedding-8b.
Voyage 4 API
Voyage AI
$0.066 per 1M input tokens
Voyage 4 Lite API
Voyage AI
$0.022 per 1M input tokens
BGE-M3 API
BAAI
$0.011 per 1M input tokens
Text Embedding 3 Small API
OpenAI
$0.022 per 1M input tokens
Text Embedding 3 Large API
OpenAI
$0.144 per 1M input tokens
Browse the full catalog — every model with its provider and per-unit price.