--- title: Google: Gemma 3 27B — Multimodal LLM | ModelsLab description: Access Google: Gemma 3 27B API for 128K context, vision-language tasks, and 140+ languages. Generate advanced text and image reasoning now. url: https://modelslab-frontend-v2-927501783998.us-east4.run.app/google-gemma-3-27b canonical: https://modelslab-frontend-v2-927501783998.us-east4.run.app/google-gemma-3-27b type: website component: Seo/ModelPage generated_at: 2026-05-13T10:31:26.279842Z --- Available now on ModelsLab · Language Model Google: Gemma 3 27B Multimodal Reasoning Power --- [Try Google: Gemma 3 27B](/models/open_router/google-gemma-3-27b-it) [API Documentation](https://docs.modelslab.com) 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](/models/open_router/google-gemma-3-27b-it). 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 ](https://docs.modelslab.com) PythonJavaScriptcURL Copy ```

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 ](https://docs.modelslab.com) ### What is Google: Gemma 3 27B? 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. ### How does Google: Gemma 3 27B API handle vision? 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. ### What context length for google gemma 3 27b? Up to 128K tokens for 27B model. Enables long documents, conversations, and multimodal transcripts. Reduces KV-cache for memory efficiency. ### Is google: gemma 3 27b multilingual? Supports 35+ languages out-of-box, pretrained on 140+. Ideal for global apps like assistants and translation. Handles diverse linguistic tasks accurately. ### Best Google: Gemma 3 27B alternative? Google: Gemma 3 27B outperforms larger models on benchmarks like LM Arena. Runs on consumer GPUs unlike heavier alternatives. Quantized versions boost speed. ### Google gemma 3 27b api pricing? 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 27B](/models/open_router/google-gemma-3-27b-it) [API Documentation](https://docs.modelslab.com) --- *This markdown version is optimized for AI agents and LLMs.* **Links:** - [Website](https://modelslab.com) - [API Documentation](https://docs.modelslab.com) - [Blog](https://modelslab.com/blog) --- *Generated by ModelsLab - 2026-05-13*