Gemma 2 9B

Google chattool_use

API ID: google/gemma-2-9b-it

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Input Price
$0.03
/1M tokens
Output Price
$0.09
/1M tokens

About Gemma 2 9B

Gemma 2 9B by Google is an advanced, open-source language model that sets a new standard for efficiency and performance in its size class. Designed for a wide variety of tasks, it empowers developers and researchers to build innovative applications, while maintaining accessibility, safety, and cost-effectiveness. See the [launch announcement](https://blog.google/technology/developers/google-gemma-2/) for more details. Usage of Gemma is subject to Google's [Gemma Terms of Use](https://ai.google.dev/gemma/terms).

📊
Price Ranking
#604 lowest price among 1240 Chat models

Model Specifications

Context Length
8k
Max Output
—
Release Date
2024-06-28
Capabilities
chat tool_use
Input Modalities
text
Output Modalities
text

Best For

  • Conversations, content writing, general assistance

Consider Alternatives For

  • Image understanding (needs vision capability)

💰 Real-World Cost Examples

Estimated monthly costs for common use cases

Personal AI Assistant
$0.04
/month
50 conversations/day, ~500 tokens each
Customer Service Bot
$1.26
/month
1000 tickets/day, ~800 tokens each
Calculate Your Custom Usage

Google Model Lineup

Compare all models from Google to find the best fit

Model Input Output Context Capabilities
Gemma 2 9B Current Free Free 8k chat tool_use
Gemma 3n 4B Free Free 33k chat
Gemini 2.5 Flash Image Preview (Nano Banana) Free Free 33k chat vision image_gen
Gemma 3n 2B (free) Free Free 8k chat tool_use
Gemma 1 2B Free Free 8k chat
Gemma 1 2B Free Free 8k chat
View All Google Models →

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💡 Cheaper Alternatives

Same Brand (Google)

Gemma 3 4B
$0.02 $0.07 131k

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 Gemma 2 9B API

Google AI Python SDK 
import google.generativeai as genai

genai.configure(api_key="YOUR_API_KEY")
model = genai.GenerativeModel("gemma-2-9b-it")

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

Resources

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