Gemini 1.5 Flash
Approved Data Classifications
Description
Gemini 1.5 Flash is Google's lower-latency multimodal model for high-volume workloads. It was released on May 14, 2024 and supports a 1 million-token context window.
Capabilities
| Model | Release Date | Input | Output | Context Length | Cost (per 1 million tokens) |
|---|---|---|---|---|---|
| gemini-1.5-flash | May 14 2024 | Text, Image, Audio, Video | Text | 1,000,000 | $.15/1M input $0.60/1M output |
info
1Mrepresents 1 Million Tokens- All prices listed are based on 1 Million Tokens
Availability
Cloud Provider
Usage
- curl
- python
- javascript
curl -X POST https://api.ai.it.ufl.edu/v1/chat/completions \
-H "Content-Type: application/json" \
-H "Authorization: Bearer <API_TOKEN>" \
-d '{
"model": "gemini-1.5-flash",
"messages": [
{
"role": "system",
"content": "You are a helpful assistant."
},
{
"role": "user",
"content": "Write a haiku about an Alligator."
}
]
}'
from openai import OpenAI
client = OpenAI(
api_key="your_api_key",
base_url="https://api.ai.it.ufl.edu/v1"
)
response = client.chat.completions.create(
model="gemini-1.5-flash", # model to send to the proxy
messages = [
{ role: "system", content: "You are a helpful assistant." },
{
"role": "user",
"content": "Write a haiku about an Alligator."
}
]
)
print(response.choices[0].message)
import OpenAI from 'openai';
const openai = new OpenAI({
apiKey: 'your_api_key',
baseURL: 'https://api.ai.it.ufl.edu/v1'
});
const completion = await openai.chat.completions.create({
model: "gemini-1.5-flash",
messages: [
{ role: "system", content: "You are a helpful assistant." },
{
role: "user",
content: "Write a haiku about an Alligator.",
},
],
});
print(completion.choices[0].message)
References
https://ai.google/- LLM Stats
https://llm-stats.com- Artificial Analysis
https://artificialanalysis.ai