Gemini 2.0 Flash Lite

Google chatvisionvideoaudioreasoningtool_use Long

API ID: google/gemini-2.0-flash-lite-001

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Input Price
$0.07
/1M tokens
Output Price
$0.30
/1M tokens

About Gemini 2.0 Flash Lite

Gemini 2.0 Flash Lite is a budget-friendly general-purpose model from Google with ultra-long context (1.0M), suitable for conversations, content creation, and general AI tasks.

💰
Price Ranking
#350 lowest price among 599 Chat models

Model Specifications

Context Length
1.0M
Max Output
8k
Release Date
2025-02-25
Capabilities
chat vision video audio reasoning tool_use
Input Modalities
textimagefileaudiovideo
Output Modalities
text

Best For

  • Complex reasoning, math problems, multi-step logic
  • Image analysis, document understanding, visual Q&A
  • Conversations, content writing, general assistance

Consider Alternatives For

  • Simple Q&A (cheaper models available)

💰 Real-World Cost Examples

Estimated monthly costs for common use cases

Personal AI Assistant
$0.12
/month
50 conversations/day, ~500 tokens each
Customer Service Bot
$3.82
/month
1000 tickets/day, ~800 tokens each
Data Analysis Pipeline
$5.29
/month
500 analyses/day, ~2k tokens each
Calculate Your Custom Usage

Google Model Lineup

Compare all models from Google to find the best fit

Model Input Output Context Capabilities
Gemini 2.0 Flash Lite Current Free Free 1.0M chat vision video audio reasoning tool_use
Gemma 3 4B Free Free 96k chat vision tool_use
Gemma 1 2B Free Free 8k chat
Gemma 3 1B Free Free 32k chat vision
Gemini Experimental 1121 Free Free 41k chat vision
Gemini Experimental 1114 Free Free 41k chat vision
View All Google Models →

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💡 Cheaper Alternatives

Same Brand (Google)

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Gemma 3 4B
$0.02 $0.07 96k
Gemma 2 9B
$0.03 $0.09 8k

Cross Brand

GTE-Base Other
$0.0050 Free 512
E5-Base-v2 Other
$0.0050 Free 512
paraphrase-MiniLM-L6-v2 Other
$0.0050 Free 512

🚀 Quick Start

Get started with Gemini 2.0 Flash Lite API

Google AI Python SDK 
import google.generativeai as genai

genai.configure(api_key="YOUR_API_KEY")
model = genai.GenerativeModel("gemini-2.0-flash-lite-001")

response = model.generate_content("Hello!")
print(response.text)

Resources

Continue Your Decision

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