Live technical benchmark comparing token limits, input/output API pricing, and modalities.
openai/gpt-5.6-terra
google/gemini-3.1-pro
The primary differentiator in developer workflow design is context retention capacity. OpenAI: GPT-5.6 Terra offers a context window of 1,050,000 tokens, while Gemini 3.1 Pro supports up to 2,000,000 tokens.
This gives Gemini 3.1 Pro a substantial advantage of 2x larger prompt processing capacity, making it the ideal choice for loading massive codebases, long runbooks, or extensive research data.
Evaluating pricing metrics is critical for running high-frequency background cron workflows.For input queries, OpenAI: GPT-5.6 Terra costs $2.50 per 1M tokens, compared to $1.25 per 1M tokens for Gemini 3.1 Pro.
Gemini 3.1 Pro is the more cost-effective choice for input prompts, yielding savings of 50% compared to OpenAI: GPT-5.6 Terra. Similarly, output generations are cheaper on Gemini 3.1 Pro ($5.00 vs $15.00), representing a savings of 67% on completion tokens.
Gemini 3.1 Pro is better for large document parsing due to its larger context capacity of 2,000,000 tokens, enabling it to fit approximately 2x more content than OpenAI: GPT-5.6 Terra in a single prompt.
Gemini 3.1 Pro is more budget-friendly for prompt inputs, costing $1.25 per million tokens (a saving of 50%). For output completion tokens, Gemini 3.1 Pro is more cost-effective ($5.00 per 1M tokens).
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