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Available now on ModelsLab · Language Model

Google: Gemma 3 27BMultimodal Reasoning Power

Deploy Gemma 3 27B Now

Vision-Language

Process Images Text

Handles 896x896 images with Pan&Scan for detailed visual reasoning in Google: Gemma 3 27B API.

128K Context

Long-Document Analysis

Supports 128K tokens for complex reasoning and summarization using Google: Gemma 3 27B model.

140+ Languages

Global Multilingual

Out-of-box support for 35+ languages, pretrained on 140+ via Google gemma 3 27b.

Examples

See what Google: Gemma 3 27B can create

Copy any prompt below and try it yourself in the playground.

Code Review

Analyze this Python function for bugs and suggest optimizations: def fibonacci(n): if n <= 1: return n else: return fibonacci(n-1) + fibonacci(n-2)

Document Summary

Summarize key points from this 10-page research paper on quantum computing advancements, focusing on practical applications.

Visual Q&A

Describe the objects, scene layout, and mood in this image of a modern city skyline at dusk, then suggest a caption.

Multilingual Translation

Translate this technical spec from English to Japanese, then explain quantum entanglement in simple terms: [insert spec text].

For Developers

A few lines of code.
27B Power. Single Call.

ModelsLab handles the infrastructure: fast inference, auto-scaling, and a developer-friendly API. No GPU management needed.

  • Serverless: scales to zero, scales to millions
  • Pay per token, no minimums
  • Python and JavaScript SDKs, plus REST API
import requests
response = requests.post(
"https://modelslab.com/api/v7/llm/chat/completions",
json={
"key": "YOUR_API_KEY",
"prompt": "",
"model_id": ""
}
)
print(response.json())

FAQ

Common questions about Google: Gemma 3 27B

Read the docs

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Start generating with Google: Gemma 3 27B on ModelsLab.