Gemini 1.5 Flash

Approved Data Classifications

Description

Gemini 1.5 Flash is a lightweight and highly efficient multimodal AI model developed by Google DeepMind, designed to excel in high-volume, low-latency tasks. Launched in May 2024, this model features a context window of up to 1 million tokens, enabling it to process extensive inputs such as long documents, images, and videos effectively. Gemini 1.5 Flash is optimized for speed and cost-efficiency, making it ideal for applications that require rapid responses, such as summarization, data extraction, and real-time chat interactions. The model leverages a distillation process from its larger counterpart, Gemini 1.5 Pro, ensuring that it retains impressive performance while being more accessible for developers looking to implement AI solutions at scale. With its ability to handle multimodal reasoning and deliver high-quality outputs across various tasks, Gemini 1.5 Flash represents a significant advancement in the Gemini model family, catering to the needs of businesses and developers aiming for efficient AI integration.

Capabilities

Model	Training Data	Input	Output	Context Length	Cost (per 1 million tokens)
gemini-1.5-flash	February 2024	Image, Text	Text	1,000,000	$.15/1M input $0.60/1M output

info

• 1M represents 1 Million Tokens
• All prices listed are based on 1 Million Tokens

Availability

Cloud Provider

Usage

curl

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."
        }
    ]
}'

python

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)

javascript

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)