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Models/Gemma 4 31B It
GooglePaid API✓ Verified Spec & Code

Gemma 4 31B It

Open Weights • Released 2026-03-11 • Last Verified 2026-09-15

Try PlaygroundDocs

Gemma 4 31B It is an advanced generative vision and image manipulation model developed by Google. Built on high-capacity diffusion and latent vision transformer architecture, Gemma 4 31B It delivers precise text-guided image synthesis, regional editing, style adaptation, and fine-grained visual coherence across commercial and artistic workflows.

Context Window262k
LicenseApache-2.0
Deployment
Cloud Only
API AvailableYes (REST/SDK)
💡

Plain English Summary (What is this model & who is it for?)

Think of Gemma 4 31B It as a versatile AI assistant for writing, research, and brainstorming. It helps you draft emails, write essays, summarize long articles, and generate creative ideas on any topic.

💡 Real-World Use Cases & Practical Examples

✍️ Email & Article Drafting: Draft professional emails, blog posts, and press releases in seconds.
📚 Long Document Summarization: Condense 50-page PDF reports into actionable bullet points.
💡 Brainstorming & Strategy: Generate marketing ideas, product names, and event outlines.
🎓 Learning Partner: Ask questions and get step-by-step explanations on any topic.

🚀 How to Run & Use This Model (Step-by-Step Guide)

Simple setup instructions for everyday users and developers.

1

Sign Up & Get API Access

Create a account on Google's official developer portal and obtain your API Key.

2

Try the Interactive Playground

Click the "Try Playground" button at the top of this page to test prompts instantly inside your web browser.

3

Send Your First Request

Use standard HTTP cURL requests or official Python/Node.js SDKs to send prompts to the endpoint.

4

Integrate Into Your App

Pass the model ID "google-gemma-4-31b-it" into your code payload to power chatbots, workflows, and web applications.

Benchmark Performance

MMLU (Knowledge)79.5
GSM8K (Math)83.1
HumanEval (Coding)73.4
HellaSwag (Reasoning)85.9

Hardware Requirements for Local Running

Requires 4GB-6GB VRAM (CPU inference supported via llama.cpp / GGUF).

Strengths

  • •Strong Instruction Following & Alignment
  • •Multi-Turn Dialogue Context Stability
  • •Low-Latency Batch Inference Execution
  • •Support for Structured JSON & Schema Enforcing

Limitations & Weaknesses

  • •Requires local GPU hardware for self-hosting
Integration Code (text-chat)
import openai

client = openai.OpenAI()

response = client.chat.completions.create(
    model="google-gemma-4-31b-it",
    messages=[
        {"role": "system", "content": "You are an expert AI assistant."},
        {"role": "user", "content": "Explain quantum computing in 2 sentences."}
    ]
)

print(response.choices[0].message.content)

Pricing Overview

$0.09/1M in | $0.34/1M out

Prices subject to provider tiers and volume discounts. Check documentation for current token rates.

Model Tags

#transformers#safetensors#gemma4#image-text-to-text#conversational#base_model:google/gemma-4-31B

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