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Available now on ModelsLab · Language Model

Google: Gemma 3 12B (free)Gemma 3 12B Free

Run Gemma 3 Efficiently

Multimodal Input

Vision-Language Processing

Handles images, text, videos with 128k token context window.

140+ Languages

Global Multilingual Support

Supports over 140 languages for worldwide applications.

Function Calling

Structured Outputs

Enables agentic workflows and complex task automation.

Examples

See what Google: Gemma 3 12B (free) can create

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

Code Review

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

Math Proof

Prove that the sum of the first n natural numbers is n(n+1)/2 using mathematical induction.

Tech Summary

Summarize the key features of quantum computing hardware from recent advancements.

Data Analysis

Analyze this dataset on renewable energy trends: [2023: Solar 45%, Wind 30%, Hydro 25%]; predict 2025 growth.

For Developers

A few lines of code.
Gemma 3. One API 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 12B (free)

Read the docs

Gemma 3 12B is a lightweight multimodal LLM from Google with 128k context. It supports vision-language tasks and runs on single GPU. Free access via API providers.

Integrate via OpenAI-compatible endpoints. Supports completion API with zero cost on select providers. Handles up to 128k tokens input.

Yes, processes vision-language inputs and text outputs. Analyzes images, text, short videos.

Best free option for Gemma 3 12B via API. Outperforms similar sizes in reasoning and multilingual tasks.

Yes, includes function calling for structured outputs. Builds agentic AI workflows.

Up to 128k tokens. Processes vast information for complex reasoning.

Ready to create?

Start generating with Google: Gemma 3 12B (free) on ModelsLab.