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Gemini 1.5 Pro vs GPT-4o: Context Window Comparison

Google's Gemini 1.5 Pro features a 2 million token context window, dwarfing GPT-4o's 128k window. However, this massive capacity introduces specific cost and latency trade-offs. Let's compare the context limits of Gemini 1.5 Pro and GPT-4o.

Run the Calculations Locally

Test your operational cost parameters on the interactive dashboard.

Launch the Context Window Calculator

1. Context Window Size Comparison

Gemini 1.5 Pro's context limit is 15x larger than GPT-4o's (2M vs 128k tokens). This allows sending hours of audio/video or entire code repositories in a single request, which is impossible on OpenAI's APIs.

2. Recall Accuracy and Retrieval Limits

Google's evaluations show Gemini 1.5 Pro maintains 99% recall accuracy across its entire 2 million token context. However, retrieval latency scales with context size, with queries taking up to 30 seconds to generate responses.

3. Pricing Tiers and Caching Discounts

Gemini 1.5 Pro input costs double for requests exceeding 128k tokens. Google offers prompt caching (50% discount on cache-hits over 32k tokens) to help manage the costs of processing large contexts.

Frequently Asked Questions

Is Gemini Pro's 2M context window practical?

Yes, for complex reasoning or document analysis tasks where context is tightly integrated. For simple workflows, it is faster and cheaper to use RAG.

Does GPT-4o support 1 million tokens?

No. OpenAI's GPT-4o is capped at a 128k context window, with no options to exceed this limit.