Moduck

Baai: BGE M3

Multilingual embedding model combining dense, sparse, and multi-vector retrieval

Model lab
Baai
Model family
bge

Model resources

Modalitiestext → text
Context window8,192
Maximum output—
InputUSD 0.008 / 1M tokens

Quickstart

Use your Moduck API Key, set the API base URL to https://api.moduck.ai/v1, and set the model parameter to baai/bge-m3.

import os
import requests

base_url = "https://api.moduck.ai/v1"
api_key = os.environ["MODUCK_API_KEY"]
model_id = "baai/bge-m3"

response = requests.post(
    f"{base_url}/chat/completions",
    headers={
        "Authorization": f"Bearer {api_key}",
        "Content-Type": "application/json",
    },
    json={
        "model": model_id,
        "messages": [{"role": "user", "content": "Hello!"}],
        "stream": False,
    },
    timeout=60,
)
response.raise_for_status()
print(response.json())

Use the familiar OpenAI-style chat request format to make model integration easier.

BGE M3 API Pricing

TypePrice information
InputUSD 0.008 / 1M tokens

Performance

Performance trends

Request throughput13.9 requests/minCurrent
Queue wait0.9 sCurrent
Completion time5.6 sCurrent
Request throughput
Current13.9 requests/min
Window average14.8 requests/min
Queue wait
Current0.9 s
Window average0.9 s
Completion time
Current5.6 s
Window average6.0 s
Tail completion time (P99)
Current13.2 s
Window average14.0 s
Retry rate
Current0.9%
Window average1.0%
Error rate
Current0.0%
Window average0.1%

Availability

Uptime100%At least one provider responded
Availability100%Requests actually served
Error rate0%Share of failed requests
Served requests, hour by hour
24 hours agoNow

BGE M3 Compare models

ModelInput priceOutput priceContext windowCapabilities
BGE M3This pageUSD 0.008 / 1M tokensNot billed on output8,192Specialized model
Qwen3 Embedding 8BUSD 0.056 / 1M tokensNot billed on output32,768Specialized model
Llama Nemotron Embed 1B v2Price currently unavailablePrice currently unavailable8,192Specialized model

Model specifications

Input
text
Output
text
Context window
8,192
Maximum output
—
Release date
2024-01-30
Attachments
No
Reasoning
No
Tool calling
No
Temperature setting
No
Open weights
Yes

Frequently asked questions

What is BGE M3 for?

Multilingual embedding model combining dense, sparse, and multi-vector retrieval

What inputs and outputs does BGE M3 support?

Recorded inputs: text; outputs: text.

How is BGE M3 priced?

The pricing table shows the current recorded Moduck price. For example: Input USD 0.008 / 1M tokens. See the pricing table for all units, variants, and conditions.

What specifications are recorded for BGE M3?

Current model records list Context window 8,192 tokens.

What model parameter does the Quickstart use?

The example uses baai/bge-m3. This value comes from the page identifier and is not confirmed as a callable Moduck public ID.

Can I call this model through the Moduck API now?

This page has no verified Moduck API call for this model. A Quickstart example or reserved ID does not establish access; check the models available to your account.