gemma-3-27b-it

completions

byparasail

gemma-3-27b-it

completions

Published by: googleProvider:

parasail

Gemma 3 introduces multimodality, supporting vision-language input and text outputs. It handles context windows up to 128k tokens, understands over 140 languages, and offers improved math, reasoning, and chat capabilities, including structured outputs and function calling. Gemma 3 27B is Google's latest open source model, successor to [Gemma 2](google/gemma-2-27b-it)

Released

Mar 12, 2025

Knowledge

Sep 13, 2024

License

Gemma

Context

131072

Input

$0.1 / 1M tokens

Output

$0.4 / 1M tokens

Accepts: text, image

Returns: text

Released Mar 12, 2025Knowledge Cutoff: Sep 13, 2024License: Gemma

Context: 131072 Input: $0.1 / 1M tokensOutput: $0.4 / 1M tokensAccepts: text, imageReturns: text

Access gemma-3-27b-it through LangDB AI Gateway

Recommended

Integrate with google's gemma-3-27b-it and 250+ other models through a unified API. Monitor usage, control costs, and enhance security.

Unified API

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Instant Setup

99.9% Uptime

10,000+Monthly Requests

Benchmark Results for gemma-3-27b-it

Category Performance Scores:

Academia: Score 32.30 (Top 66% - Rank #214)
Finance: Score 39.40 (Top 50% - Rank #162)
Marketing: Score 16.23 (Top 76% - Rank #247)
Maths: Score 56.80 (Top 47% - Rank #153)
Programming: Score 17.40 (Top 76% - Rank #247)
Science: Score 42.60 (Top 70% - Rank #227)
Writing: Score 14.59 (Top 76% - Rank #247)

Overall Performance: 31.33142857142857 average score across all categories

Detailed Benchmark Scores:

Benchmark	Score	Percentile	Domain
AIME	25.30	Top 48%	Mathematics
AA Coding Index	17.40	Top 76%	Programming
AAII	22.00	Top 65%	General
AA Math Index	56.80	Top 47%	Mathematics
GPQA	42.60	Top 70%	STEM (Physics, Chemistry, Biology)
HLE	4.70	Top 41%	General Knowledge
HumanEval	87.80	Top 35%	Programming
LiveCodeBench	13.70	Top 84%	Programming
MATH-500	88.30	Top 43%	Mathematics
MMLU-Pro	67.20	Top 65%	General Knowledge
SciCode	21.20	Top 68%	Scientific

HumanEval Score: 87.80 - Coding capability benchmark

GPQA Score: 42.60 - Graduate-level reasoning benchmark

Model Comparison:

Provider: parasail

Model Type: completions

Context Size: 131072 tokens

Comparing against 324 models in the database

Performance Analytics for gemma-3-27b-it

Usage Statistics (Last 8 Days):

Total Requests: 314 API calls
Average TPS: 729.05 tokens per second
Average Response Time: 996.20ms
Average Time to First Token: 996.20ms
Total Cost: $0.03
Average Request Cost: $0.0001

Daily Performance Breakdown:

Date	Requests	TPS	Response Time	TTFT	Cost
9/4/2025	6	358.25	2141.90ms	2141.90ms	$0.00
9/5/2025	18	785.22	810.30ms	810.30ms	$0.00
9/6/2025	69	1226.50	750.80ms	750.80ms	$0.01
9/7/2025	14	1071.20	767.30ms	767.30ms	$0.00
9/8/2025	51	888.81	795.60ms	795.60ms	$0.00
9/9/2025	76	639.99	808.20ms	808.20ms	$0.01
9/10/2025	78	702.49	1105.20ms	1105.20ms	$0.01
9/11/2025	2	29.35	17309.50ms	17309.50ms	$0.00

Performance Summary:

Model: gemma-3-27b-it by parasail

Monitoring Period: 9/4/2025 to 9/11/2025

Average Daily Requests: 39

Peak Daily Requests: 78

Statistics

View Full Statistics

Request Volume

Daily API requests

314

Performance (TPS)

Tokens per second

729.05 tokens/s

Category Scores

Benchmark Tests

View Other Benchmarks

AIME

25.3

Mathematics

AA Coding Index

17.4

Programming

AAII

22.0

General

AA Math Index

56.8

Mathematics

GPQA

42.6

STEM (Physics, Chemistry, Biology)

HLE

4.7

General Knowledge

HumanEval

87.8

Programming

LiveCodeBench

13.7

Programming

MATH-500

88.3

Mathematics

MMLU-Pro

67.2

General Knowledge

SciCode

21.2

Scientific

Metric	AIME	AA Coding Index	AAII	AA Math Index	GPQA	HLE	HumanEval	LiveCodeBench	MATH-500	MMLU-Pro	SciCode
Score	25.3	17.4	22.0	56.8	42.6	4.7	87.8	13.7	88.3	67.2	21.2

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Code Examples

Integration samples and API usage

Code Samples for gemma-3-27b-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-3-27b-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-3-27b-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-3-27b-it",
    "messages": [
        {"role": "user", "content": "Hello, how are you?"}
    ]
  }'

Model: gemma-3-27b-it

Provider: parasail

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

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gemma-3-27b-it by parasail - AI Model Details, Pricing, and Performance Metrics

gemma-3-27b-it

gemma-3-27b-it

Access gemma-3-27b-it through LangDB AI Gateway

Statistics

Category Scores

Benchmark Tests

Compare with Similar Models

Code Examples

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