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Google: Gemma 3 27BMultimodal Reasoning Power

Try Google: Gemma 3 27BAPI Documentation

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
API Documentation 
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

Google: Gemma 3 27B is a 27B parameter multimodal LLM from Google DeepMind. It processes text and images, outputs text, with 128K context. Fits single GPU for efficient deployment.

Uses SigLIP encoder on 896x896 images with Pan&Scan cropping. Encodes to 256 tokens per image for visual QA and reasoning. Supports detailed analysis across aspect ratios.

Up to 128K tokens for 27B model. Enables long documents, conversations, and multimodal transcripts. Reduces KV-cache for memory efficiency.

Supports 35+ languages out-of-box, pretrained on 140+. Ideal for global apps like assistants and translation. Handles diverse linguistic tasks accurately.

Google: Gemma 3 27B outperforms larger models on benchmarks like LM Arena. Runs on consumer GPUs unlike heavier alternatives. Quantized versions boost speed.

Available via platforms like OpenRouter at $0.08/M input, $0.16/M output tokens. Open weights enable local or cloud deployment. Check provider for exact rates.

Ready to create?

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

Try Google: Gemma 3 27BAPI Documentation