Gemini 1.5 Flash vs GPT-4o mini

A side-by-side comparison of two Small LLM models - to help you pick the right one.

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Gemini 1.5 Flash

Google

Gemini 1.5 Flash is a small, fast, and low-cost multimodal LLM from Google, designed for high-throughput tasks. It excels at handling long-context inputs (up to 1M tokens) and supports text, vision, and audio modalities. The model is optimized for scenarios where speed and cost efficiency are prioritized.
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GPT-4o mini

OpenAI

GPT-4o mini is a smaller, low-cost OpenAI model designed for high-volume tasks. It supports both text and vision inputs, making it versatile for multimodal applications. With a 128,000-token context window and 16,384-token max output, it balances capacity and affordability.

Spec comparison

Gemini 1.5 Flash GPT-4o mini
Provider Google OpenAI
Category Small LLM Small LLM
Context window 1M ctx 128K ctx
Max output 8K ctx 16K ctx
Input price $0.07 / 1M $0.15 / 1M
Output price $0.30 / 1M $0.60 / 1M
License Proprietary Proprietary
Open weights No No
Modality Text, Vision, Audio Text, Vision

Prices and specs are per provider documentation; verify current figures before relying on them.

Gemini 1.5 Flash: what it's for

Gemini 1.5 Flash is a small, fast, and low-cost multimodal LLM from Google, designed for high-throughput tasks. It excels at handling long-context inputs (up to 1M tokens) and supports text, vision, and audio modalities. The model is optimized for scenarios where speed and cost efficiency are prioritized.

Processing and summarizing long documents or reportsMultimodal content analysis (e.g., extracting insights from text, images, and audio)High-volume conversational applications where latency mattersAutomated data extraction from mixed-format inputsLow-cost prototyping for multimodal AI applications

GPT-4o mini: what it's for

GPT-4o mini is a smaller, low-cost OpenAI model designed for high-volume tasks. It supports both text and vision inputs, making it versatile for multimodal applications. With a 128,000-token context window and 16,384-token max output, it balances capacity and affordability.

High-throughput text processing (e.g., batch summarization or classification)Multimodal tasks combining text and image inputs (e.g., document analysis with embedded figures)Cost-sensitive applications requiring OpenAI's API compatibilityModerate-length content generation with structured output constraintsPre-filtering or preprocessing for downstream larger models
Full Gemini 1.5 Flash details Full GPT-4o mini details

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