multi-qa-mpnet-base-dot-v1 - API in Egypt, billed in EGP
LiveWe present a sentence transformation model that maps sentences and paragraphs to a 768-dimensional dense vector space, suitable for semantic search tasks. The model is trained on 215 million question-answer pairs from various sources, including WikiAnswers, PAQ, Stack Exchange, MS MARCO, GOOAQ, Amazon QA, Yahoo Answers, Search QA, ELI5, and Natural Questions. Our model uses a contrastive learning objective.
Modality
Embedding
Context window
512 tokens
Region
US
Weights
Open weights
Published
29 Sept 2026
Pricing
Input
0.29
EGP per 1M tokens
Output
—
EGP per 1M tokens
Monthly cost example
14.33 EGP
Illustrative estimate: 50M input + 15M output tokens per month at this model's catalog rates.
Use it via the API
multi-qa-mpnet-base-dot-v1 works with any OpenAI-compatible SDK — point the base URL at https://dev-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://dev-backend.sovereigneg.com/v1",
api_key="YOUR_API_KEY",
)
response = client.embeddings.create(
model="multi-qa-mpnet-base-dot-v1",
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://dev-backend.sovereigneg.com/v1",
apiKey: "YOUR_API_KEY",
})
const response = await client.embeddings.create({
model: "multi-qa-mpnet-base-dot-v1",
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://dev-backend.sovereigneg.com/v1/embeddings \
-H "Authorization: Bearer YOUR_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "multi-qa-mpnet-base-dot-v1",
"input": "The food was delicious and the waiter...",
"encoding_format": "float"
}'Frequently asked questions
How much does multi-qa-mpnet-base-dot-v1 cost?
0.29 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 multi-qa-mpnet-base-dot-v1?
multi-qa-mpnet-base-dot-v1 supports a context window of 512 tokens (512).
Where is multi-qa-mpnet-base-dot-v1 hosted?
multi-qa-mpnet-base-dot-v1 is served from US (US-hosted inference).
Is multi-qa-mpnet-base-dot-v1 an open-weights model?
Yes — multi-qa-mpnet-base-dot-v1 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 multi-qa-mpnet-base-dot-v1 via the API?
multi-qa-mpnet-base-dot-v1 is available through the OpenAI-compatible SovereignEG API: point your SDK's base URL at https://dev-backend.sovereigneg.com/v1 and call /v1/embeddings with model "multi-qa-mpnet-base-dot-v1" and your API key.