gemma-2-9b-it

completions

bygroq

gemma-2-9b-it

completions

Published by: googleProvider:

groq

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).

Released

Jun 27, 2024

Knowledge

Dec 30, 2023

License

Gemma

Context

8192

Input

$0.2 / 1M tokens

Output

$0.2 / 1M tokens

Accepts: text

Returns: text

Released Jun 27, 2024Knowledge Cutoff: Dec 30, 2023License: Gemma

Context: 8192 Input: $0.2 / 1M tokensOutput: $0.2 / 1M tokensAccepts: textReturns: text

Access gemma-2-9b-it through LangDB AI Gateway

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Benchmark Results for gemma-2-9b-it

Category Performance Scores:

Science: Score 35.23 (Top 91% - Rank #292)
Writing: Score 34.86 (Top 83% - Rank #266)
Academia: Score 19.45 (Top 95% - Rank #304)
Marketing: Score 36.78 (Top 76% - Rank #244)

Overall Performance: 31.579583333333336 average score across all categories

Detailed Benchmark Scores:

Benchmark	Score	Percentile	Domain
HLE	3.90	Top 81%	General Knowledge
AIME	0.00	Top 94%	Mathematics
GPQA	31.10	Top 94%	STEM (Physics, Chemistry, Biology)
MMLU	71.30	Top 82%	General Knowledge
SciCode	0.70	Top 99%	Scientific
MATH-500	51.70	Top 92%	Mathematics
MMLU-Pro	49.50	Top 90%	General Knowledge
HumanEval	40.20	Top 97%	Programming
LiveCodeBench	12.60	Top 92%	Programming
AAII	7.80	Top 97%	General

MMLU Score: 71.30 - Massive Multitask Language Understanding benchmark

HumanEval Score: 40.20 - Coding capability benchmark

GPQA Score: 31.10 - Graduate-level reasoning benchmark

Model Comparison:

Provider: groq

Model Type: completions

Context Size: 8192 tokens

Comparing against 320 models in the database

Category Scores

Benchmark Tests

View Other Benchmarks

HLE

3.9

General Knowledge

AIME

0.0

Mathematics

GPQA

31.1

STEM (Physics, Chemistry, Biology)

MMLU

71.3

General Knowledge

SciCode

0.7

Scientific

MATH-500

51.7

Mathematics

MMLU-Pro

49.5

General Knowledge

HumanEval

40.2

Programming

LiveCodeBench

12.6

Programming

AAII

7.8

General

Metric	HLE	AIME	GPQA	MMLU	SciCode	MATH-500	MMLU-Pro	HumanEval	LiveCodeBench	AAII
Score	3.9	0.0	31.1	71.3	0.7	51.7	49.5	40.2	12.6	7.8

Compare with Similar Models

Code Examples

Integration samples and API usage

Code Samples for gemma-2-9b-it

Python SDK Example:

from openai import OpenAI

client = OpenAI(
    base_url="https://api.us-east-1.langdb.ai//projects/<your_project_id>",
    api_key="<your_api_key>"
)

response = client.chat.completions.create(
    model="gemma-2-9b-it",
    messages=[
        {"role": "user", "content": "Hello, how are you?"}
    ]
)

print(response.choices[0].message.content)

TypeScript SDK Example:

import OpenAI from 'openai';

const client = new OpenAI({
    baseURL: "https://api.us-east-1.langdb.ai//projects/<your_project_id>",
    apiKey: "<your_api_key>"
});

const response = await client.chat.completions.create({
    model: "gemma-2-9b-it",
    messages: [
        { role: "user", content: "Hello, how are you?" }
    ]
});

console.log(response.choices[0].message.content);

cURL Example:

curl -X POST "https://api.us-east-1.langdb.ai//projects/<your_project_id>/v1/chat/completions" \
  -H "Authorization: Bearer <your_api_key>" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "gemma-2-9b-it",
    "messages": [
        {"role": "user", "content": "Hello, how are you?"}
    ]
  }'

Model: gemma-2-9b-it

Provider: groq

API Endpoint: $https://api.us-east-1.langdb.ai/

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Access gemma-2-9b-it through LangDB AI Gateway

Category Scores

Benchmark Tests

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Code Examples

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