bge-m3 - API in Egypt, billed in EGP
LiveBGE-M3 is a versatile text embedding model that supports multi-functionality, multi-linguality, and multi-granularity, allowing it to perform dense retrieval, multi-vector retrieval, and sparse retrieval in over 100 languages and with input sizes up to 8192 tokens. The model can be used in a retrieval pipeline with hybrid retrieval and re-ranking to achieve higher accuracy and stronger generalization capabilities. BGE-M3 has shown state-of-the-art performance on several benchmarks, including MKQA, MLDR, and NarritiveQA, and can be used as a drop-in replacement for other embedding models like DPR and BGE-v1.5.
Modality
Embedding
Context window
8K tokens
Region
US
Weights
Open weights
Published
Jul 14, 2026
Pricing
Input
0.65
EGP per 1M tokens
Output
Free
EGP per 1M tokens
Monthly cost example
32.5 EGP
Illustrative estimate: 50M input + 15M output tokens per month at this model's catalog rates.
Use it via the API
bge-m3 works with any OpenAI-compatible SDK — point the base URL at https://backend.sovereigneg.com/v1 and use your SovereignEG API key.
Run inference
OpenAI-compatible — POST /v1/embeddings — drop-in for any OpenAI SDK.
from openai import OpenAI
client = OpenAI(
base_url="https://backend.sovereigneg.com/v1",
api_key="YOUR_API_KEY",
)
response = client.embeddings.create(
model="bge-m3",
input="The food was delicious and the waiter...",
encoding_format="float",
)
vector = response.data[0].embedding
print(f"dim={len(vector)}, first 8 dims: {vector[:8]}")import OpenAI from "openai"
const client = new OpenAI({
baseURL: "https://backend.sovereigneg.com/v1",
apiKey: "YOUR_API_KEY",
})
const response = await client.embeddings.create({
model: "bge-m3",
input: "The food was delicious and the waiter...",
encoding_format: "float",
})
const vector = response.data[0].embedding
console.log(`dim=${vector.length}, first 8 dims:`, vector.slice(0, 8))curl https://backend.sovereigneg.com/v1/embeddings \
-H "Authorization: Bearer YOUR_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "bge-m3",
"input": "The food was delicious and the waiter...",
"encoding_format": "float"
}'Frequently asked questions
How much does bge-m3 cost?
0.65 EGP per 1M input tokens; Output tokens are free. Billing is metered per token in Egyptian pounds (EGP), with no minimum commitment.
What is the context window of bge-m3?
bge-m3 supports a context window of 8,192 tokens (8K).
Where is bge-m3 hosted?
bge-m3 is served from US (US-hosted inference).
Is bge-m3 an open-weights model?
Yes — bge-m3 is an open-weights model. You call it through the SovereignEG API like any other catalog model, with per-token EGP billing.
How do I use bge-m3 via the API?
bge-m3 is available through the OpenAI-compatible SovereignEG API: point your SDK's base URL at https://backend.sovereigneg.com/v1 and call /v1/embeddings with model "bge-m3" and your API key.