Google: Gemini 1.5 Flash

Image input Text input Text output Unavailable
Author's Description

Gemini 1.5 Flash is a foundation model that performs well at a variety of multimodal tasks such as visual understanding, classification, summarization, and creating content from image, audio and video. It's adept at processing visual and text inputs such as photographs, documents, infographics, and screenshots. Gemini 1.5 Flash is designed for high-volume, high-frequency tasks where cost and latency matter. On most common tasks, Flash achieves comparable quality to other Gemini Pro models at a significantly reduced cost. Flash is well-suited for applications like chat assistants and on-demand content generation where speed and scale matter. Usage of Gemini is subject to Google's [Gemini Terms of Use](https://ai.google.dev/terms). #multimodal

Key Specifications
Cost
$$
Context
1M
Parameters
500B (Rumoured)
Released
May 13, 2024
Speed
Ability
Reliability
Supported Parameters

This model supports the following parameters:

Tools Stop Frequency Penalty Presence Penalty Top P Tool Choice Response Format Temperature Seed Structured Outputs Max Tokens
Features

This model supports the following features:

Response Format Structured Outputs Tools
Performance Summary

Google's Gemini 1.5 Flash consistently ranks among the fastest models available, demonstrating exceptional speed across various benchmarks. It also offers highly competitive pricing, making it a cost-effective solution for high-volume tasks. The model exhibits outstanding reliability, achieving a 100% success rate across all evaluated benchmarks, indicating minimal technical failures. In terms of performance across categories, Gemini 1.5 Flash shows perfect accuracy in "Hallucinations (Baseline)" and "Email Classification (Baseline)," highlighting its strong ability to acknowledge uncertainty and accurately categorize information. It performs well in "General Knowledge," "Ethics," "Mathematics," "Reasoning," and "Coding," with respectable accuracy scores. A notable weakness is its performance in "Instruction Following (Baseline)," where it scored 0% accuracy, suggesting limitations in handling complex, multi-layered instructions. Its strengths lie in its speed, cost-efficiency, reliability, and strong performance in classification and factual recall, making it well-suited for applications requiring rapid, accurate responses at scale.

Model Pricing

Current Pricing

Feature Price (per 1M tokens)
Prompt $0.075
Completion $0.3
Input Cache Read $0.0188
Input Cache Write $0.158

Price History

Available Endpoints
Provider Endpoint Name Context Length Pricing (Input) Pricing (Output)
Google
Google | google/gemini-flash-1.5 1M $0.075 / 1M tokens $0.3 / 1M tokens
Google AI Studio
Google AI Studio | google/gemini-flash-1.5 1M $0.075 / 1M tokens $0.3 / 1M tokens
Benchmark Results
Benchmark Category Reasoning Strategy Free Executions Accuracy Cost Duration
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