LightweightGoogle

Gemma 3 12B

Gemma 3 12B is Google's lightweight multimodal model with text and image capabilities, featuring a 131K token context window for efficient processing tasks.

Context 131K
Tier Lightweight
Modalities text, image
Input from
$0.040 / 1M tokens
across 3 providers

API Pricing

Cheapest on Deep Infra 27% below avg
ProviderInput / 1MOutput / 1MSpeedTTFTUpdated
$0.040$0.13030.3 t/s35.2s4/4/2026
$0.040$0.13030.3 t/s35.2s4/14/2026
$0.050$0.15030.3 t/s35.2s4/14/2026
$0.090$0.29030.3 t/s35.2s4/14/2026

Prices updated daily. Last check: 4/14/2026

Model Details

General

Creator
Google
Family
Gemma
Tier
Lightweight
Context Window
131K
Modalities
Text, Image

Capabilities

Tool Calling
No
Open Source
No

Strengths & Limitations

  • Multimodal support for both text and image inputs
  • 131,072 token context window for processing long documents
  • 28.89 tokens per second output generation speed
  • Lightweight architecture reduces computational requirements
  • Part of Google's established Gemma model family
  • Balanced performance-to-efficiency ratio for moderate workloads
  • No tool calling or function execution capabilities
  • Not open source - model weights unavailable for local deployment
  • 27-second time to first token indicates slower response initiation
  • Lightweight tier limits complexity compared to flagship models

Key Features

131,072 token context window
Text and image input processing
Streaming response generation
Multimodal understanding capabilities
12-billion parameter architecture
Cross-modal reasoning between text and images

About Gemma 3 12B

Gemma 3 12B is a lightweight model from Google's Gemma family, designed to balance capability with efficiency for moderate-scale applications. As part of Google's third-generation Gemma series, this 12-billion parameter model sits in the lightweight tier, making it suitable for applications that need reasonable performance without the computational overhead of larger flagship models. The model supports both text and image inputs with a 131,072 token context window, allowing it to process substantial documents or maintain extended conversations while incorporating visual information. Performance benchmarks show an output speed of 28.89 tokens per second with a time to first token of approximately 27 seconds, indicating steady generation once processing begins. Gemma 3 12B serves applications requiring multimodal understanding at scale, such as document analysis with visual elements, content moderation, or customer service scenarios where both text and image processing are needed but computational resources are constrained compared to flagship model deployments.

Common Use Cases

Gemma 3 12B is well-suited for applications requiring multimodal processing at moderate scale, including document analysis that combines text and visual elements, content moderation across text and image platforms, educational tools that process mixed media content, and customer service systems handling both written queries and image attachments. Its lightweight architecture makes it appropriate for organizations needing multimodal capabilities without the computational costs of larger models, while the 131K context window supports processing substantial documents or maintaining extended conversations that incorporate visual information.

Frequently Asked Questions

How much does Gemma 3 12B cost per million tokens?

Gemma 3 12B pricing varies by provider and pricing type (standard vs batch). Check the pricing table above for current rates across all providers.

What is Gemma 3 12B best used for?

Gemma 3 12B excels at multimodal tasks requiring both text and image processing, such as document analysis with visual elements, content moderation, and customer service applications. Its lightweight architecture makes it ideal when you need reasonable multimodal capabilities without the computational overhead of flagship models.

Does Gemma 3 12B support tool calling or function execution?

No, Gemma 3 12B does not support tool calling or function execution capabilities. It focuses on multimodal text and image understanding rather than agentic workflows that require external tool integration.