llama-nemotron-embed-vl-1b-v2 - API in Egypt, billed in EGP
LiveThe llama-nemotron-embed-vl-1b-v2 is a high-performance multimodal embedding model designed to transform text queries and document images into dense vector representations for advanced retrieval systems. It excels at understanding complex visual content like charts, tables, and infographics.
Modality
Embedding
Context window
10K 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
llama-nemotron-embed-vl-1b-v2 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="llama-nemotron-embed-vl-1b-v2",
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: "llama-nemotron-embed-vl-1b-v2",
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": "llama-nemotron-embed-vl-1b-v2",
"input": "The food was delicious and the waiter...",
"encoding_format": "float"
}'Frequently asked questions
How much does llama-nemotron-embed-vl-1b-v2 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 llama-nemotron-embed-vl-1b-v2?
llama-nemotron-embed-vl-1b-v2 supports a context window of 10,240 tokens (10K).
Where is llama-nemotron-embed-vl-1b-v2 hosted?
llama-nemotron-embed-vl-1b-v2 is served from US (US-hosted inference).
Is llama-nemotron-embed-vl-1b-v2 an open-weights model?
Yes — llama-nemotron-embed-vl-1b-v2 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 llama-nemotron-embed-vl-1b-v2 via the API?
llama-nemotron-embed-vl-1b-v2 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 "llama-nemotron-embed-vl-1b-v2" and your API key.
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