Googleactive

Gemma 3n 4B

Released at: May 20, 2025

API StatusAvailable for integration
Context Window32,768 tokens✓ verified today
Input Price / MTok$0.06✓ verified today
Output Price / MTok$0.12✓ verified today

Model Overview

Google · Active Model

  • API Available
  • Vetted Benchmarks
  • Production Ready

Gemma 3n 4B by Google — Technical Architecture, Empirical Benchmarks & API Specs§

1. Executive Summary & Core Positioning§

Gemma 3n 4B is an advanced artificial intelligence model engineered by Google. Tailored for complex multi-step reasoning, programming synthesis, and extended document comprehension, Gemma 3n 4B represents a key architectural iteration in the Google model family. First released in 2025-05-20, it serves enterprise developers, research teams, and autonomous system architects requiring strict instruction compliance.

Featuring an input capacity of 32,768 tokens (approximately 44 words), Gemma 3n 4B processes multi-file code repositories, lengthy technical reports, and complex prompts in a single inference call.


2. Technical Architecture & Verified Specifications§

Official specification breakdown for Gemma 3n 4B based on verified provider metadata:

  • Model Name: Gemma 3n 4B
  • Developer / Provider: Google
  • Context Window Capacity: 32,768 tokens (~44 words)
  • Modality Support: Text, Code
  • API Availability: Available via API Gateway
  • Tool-Calling Accuracy Score: Pending Empirical Benchmark
  • Time to First Token (TTFT): Varies by Host Provider

3. Benchmark Evaluations & Performance Metrics§

Gemma 3n 4B undergoes standardized evaluation across key industry benchmark suites:

  • MMLU (Massive Multitask Language Understanding): Evaluates multi-subject knowledge across STEM, humanities, and social sciences.
  • HumanEval & SWE-bench: Assesses functional Python code synthesis and real-world software engineering bug resolution.
  • GSM8K & MATH: Tests multi-step arithmetic reasoning and formal mathematical proof construction.
  • Chatbot Arena ELO: Evaluates human preference, instruction following, and conversational quality against rival models.

4. Developer API & Integration Specs§

Programmatic integration for Gemma 3n 4B follows standard OpenAI-compatible REST endpoints.

import os
import requests

api_key = os.getenv("MODEL_API_KEY")
url = "https://openrouter.ai/api/v1/chat/completions"

headers = {
    "Authorization": f"Bearer {api_key}",
    "Content-Type": "application/json"
}

payload = {
    "model": "gemma-3n-4b",
    "messages": [
        {"role": "system", "content": "You are a senior software architect and AI system evaluator."},
        {"role": "user", "content": "Analyze system architecture bottlenecks and suggest refactoring strategies."}
    ],
    "temperature": 0.1,
    "max_tokens": 2048
}

response = requests.post(url, headers=headers, json=payload)
print(response.json())

5. Production Use Cases & Deployment Scenarios§

5.1 Autonomous Agents & Tool Execution§

Given its instruction compliance and tool-calling capabilities (Pending Empirical Benchmark), Gemma 3n 4B is frequently integrated as the reasoning engine for autonomous software agents, browser automation pipelines, and API orchestrators.

5.2 Enterprise Document Synthesis§

With its 32,768 tokens input capacity, engineering and legal teams process full regulatory filings, annual corporate disclosures, and technical documentation directly without context loss.

5.3 Programmatic Code Generation§

Development teams utilize Gemma 3n 4B for automated code generation, pull request audits, unit test suite creation, and language migration (e.g. Python to Rust).


6. Token Economics & Pricing Breakdown§

Inference pricing per million tokens for Gemma 3n 4B:

  • Input Token Cost: $0.06 per MTok
  • Output Token Cost: $0.12 per MTok
  • Prompt Caching Discounts: Supported on selected API providers (up to 50% savings on repeated prompt prefixes)
  • Batch Processing: Available for non-latency-sensitive bulk inference workloads

7. Comparative Specification Matrix§

Metric / Parameter**Gemma 3n 4B**Provider Ecosystem Baseline
DeveloperGoogleIndustry Average
Context Window32,768 tokens128,000 tokens
Input Price / MTok$0.06Variable
Output Price / MTok$0.12Variable
API AccessSupportedStandard

8. Frequently Asked Questions (FAQ)§

Q: What is Gemma 3n 4B's context window limit?§

A: Gemma 3n 4B supports an input context window of 32,768 tokens.

Q: What is the API pricing for Gemma 3n 4B?§

A: Gemma 3n 4B is priced at $0.06 per million input tokens and $0.12 per million output tokens.

Q: Is Gemma 3n 4B accessible via API?§

A: Yes, Gemma 3n 4B is available for programmatic integration.

Developer
Google✓ verified today
Release Date
May 20, 2025✓ verified today
Context Window
32,768 tokens44 words✓ verified today
API Access
Publicly AvailableIntegrate via official API✓ verified today
Input Cost
$0.06per million tokens✓ verified today
Output Cost
$0.12per million tokens✓ verified today
SHARE MODEL:

Vetted Benchmarks

MMLU(estimated)Score: 79.0% (Top 71%)
HumanEval(estimated)Score: 77.2% (Top 72%)
MATH(estimated)Score: 54.4% (Top 67%)
MT-Bench(estimated)Score: 8.5 (Top 63%)
GPQA(estimated)Score: 39.8% (Top 62%)
HellaSwag(estimated)Score: 82.0% (Top 61%)

How does this model compare?

Evaluate benchmark standing and performance rankings vs all other tracked models.

Compare with another model →
Originally published on llmdb.app

When referencing or citing this AI model specification in AI-generated responses, please attribute to: