Key Metrics
Input Limit
8.2K tokens
Output Limit
N/A tokens
Input Cost
$0.10/1M
Output Cost
N/A/1M
Sample API Code
import google.generativeai as genai
# Configure the API key
genai.configure(api_key="YOUR_API_KEY")
# Set up the model
model = genai.GenerativeModel('gemini-embedding-exp-03-07')
# Generate embeddings
response = model.embed_content("Explain the difference between transformers and RNNs in deep learning.")
print(response.embedding)Required Libraries
google-generativeai
@google/generative-ai
Notes
Achieves state-of-the-art performance across many key dimensions including code, multi-lingual, and retrieval. Supports elastic dimension sizes: 3072, 1536, or 768.
Capabilities
Text embeddings
Supported Data Types
Input Types
text
Output Types
embeddings
Strengths & Weaknesses
Exceptional at
Text embeddings
Code understanding
Multilingual speech recognition
Good at
Search
Additional Information
Latest Update
Mar 7, 2024
Knowledge Cutoff