Gemini 1.5 Flash
Available standardFast, efficient multimodal model for high-volume tasks
Released May 14, 2024
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
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
| Metric | Flash | Pro |
|---|---|---|
| Response Time | 120ms | 450ms |
| Tokens/Second | 150 | 65 |
| Input Cost | $0.075/M | $1.25/M |
| Context Window | 1M | 2M |
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
Other Google AI Models
See all models- Gemini 2.0 Flash
- Google's fastest multimodal model with native tool use
- Context
- 1M
- Speed
- N/A
- TTFT
- N/A
- Gemini 2.0 Flash Thinking
- Experimental reasoning model with transparent thought process
- Context
- 1M
- Speed
- N/A
- TTFT
- N/A
- Gemini 1.5 Pro
- Google's flagship model with 2M token context window
- Context
- 2M
- Speed
- N/A
- TTFT
- N/A
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