Google AI

Gemini 1.5 Flash

Available standard

Fast, efficient multimodal model for high-volume tasks

Released May 14, 2024

Context Window
1M
TTFT
N/A
Speed
N/A
Max Output
8K
Training Cutoff
Nov 2023

Last tested: 2026-01-15

About

Gemini 1.5 Flash is Google's speed-optimized multimodal model, delivering exceptional performance at a fraction of the cost of Gemini 1.5 Pro. With a 1 million token context window and sub-second response times, it's ideal for real-time applications, high-volume processing, and cost-sensitive deployments.

Capabilities

vision audio video function-calling streaming json-mode

Pricing

Input
$0.075/M
per 1M tokens
Output
$0.30/M
per 1M tokens

Static pricing

Details

Overview

Gemini 1.5 Flash brings the power of Google’s Mixture-of-Experts architecture to cost-conscious applications. Designed for speed and efficiency, it maintains strong quality while dramatically reducing latency and cost compared to Gemini 1.5 Pro.

Key Features

Optimized for Speed

With response times under 200ms for most queries, Gemini 1.5 Flash enables real-time applications that were previously impractical with larger models.

Cost Efficiency

At $0.075 per million input tokens, Flash is approximately 17x cheaper than Pro, making it viable for high-volume production workloads.

Full Multimodal Support

Despite its efficiency focus, Flash retains complete multimodal capabilities including image, audio, and video understanding.

Extended Context

The 1 million token context window provides ample room for complex tasks while maintaining fast response times.

Performance Comparison

MetricFlashPro
Response Time120ms450ms
Tokens/Second15065
Input Cost$0.075/M$1.25/M
Context Window1M2M

Use Cases

  • Chatbots: Real-time conversational AI with multimodal inputs
  • Content Moderation: High-volume image and text classification
  • Data Extraction: Parse and structure documents at scale
  • Summarization: Fast summarization of articles, emails, and reports
  • Translation: Efficient multilingual content processing

When to Choose Flash vs Pro

Choose Flash when:

  • Response time is critical
  • Processing high volumes of requests
  • Budget constraints are significant
  • Tasks are well-defined and don’t require maximum capability

Choose Pro when:

  • Maximum reasoning capability is needed
  • Working with very long contexts (>1M tokens)
  • Complex multi-step analysis is required
  • Quality is more important than speed

Best Practices

  • Batch similar requests to maximize throughput
  • Use structured output (JSON mode) for consistent parsing
  • Combine with function calling for agentic workflows
  • Monitor latency and quality metrics to optimize prompt design
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