Overview

Gemma 3 27B delivers exceptional performance for complex reasoning and long-context tasks within an efficient parameter footprint. Engineered for seamless integration, this model supports a 128,000 token context window, enabling deep document analysis and extended conversation history without performance degradation. Developers can access this capability immediately through standardized API endpoints, requiring minimal configuration to initiate the first request within minutes. The FP16 quantization ensures high precision while maintaining inference speed, making it ideal for production environments demanding both accuracy and latency control.

For research pipelines, Gemma 3 demonstrates competitive benchmarks across multilingual tasks, including robust Arabic and English proficiency. This makes it a versatile choice for global applications requiring nuanced language understanding. Our platform provides transparent usage metrics with a 3x credit multiplier relative to base rates, allowing precise cost forecasting for scaling operations.

Available on the starter tier, this model is production-ready out of the box, eliminating the need for extensive fine-tuning before deployment. Teams can rely on consistent output quality for customer-facing agents or data extraction workflows while managing budget efficiency through our clear credit structure. The GEMMA license facilitates broad commercial usage, ensuring compliance for enterprise deployments.

Specifications

Display Name Gemma 3 27B

Family Gemma

Category Vision

Parameters 27B

Context Window 128,000 tokens

Quantization FP16

License GEMMA

Min Tier Starter

Status Available

Pricing

3×

credits per token

1K 3,000 Credits

10K 30,000 Credits

100K 300,000 Credits

View Pricing Plans

Code Examples

from openai import OpenAI

client = OpenAI(
    base_url="https://llmapi.resayil.io/v1/",
    api_key="YOUR_API_KEY"
)

response = client.chat.completions.create(
    model="gemma3:27b",
    messages=[
        {"role": "user", "content": "Hello!"}
    ]
)

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

const response = await fetch(
    "https://llmapi.resayil.io/v1/chat/completions",
    {
        method: "POST",
        headers: {
            "Content-Type": "application/json",
            "Authorization": "Bearer YOUR_API_KEY"
        },
        body: JSON.stringify({
            model: "gemma3:27b",
            messages: [
                { role: "user", content: "Hello!" }
            ]
        })
    }
);

const data = await response.json();
console.log(data.choices[0].message.content);

curl https://llmapi.resayil.io/v1/chat/completions \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -d '{
    "model": "gemma3:27b",
    "messages": [
      {"role": "user", "content": "Hello!"}
    ]
  }'

Use Cases

Summarizing long documents and extracting key insights quickly

Interactive coding assistance and debugging complex software projects

Customer support chatbot for handling detailed customer inquiries

Analyzing extensive legal contracts for specific compliance issues

Generating creative writing stories with consistent character development

In-Depth Guide

Full Guide

Complete Guide to Gemma 3 27B — LLM Resayil

Gemma 3 27B