OPENAI VS GOOGLE

GPT-5.6 Terra vs Gemini 3.1 Pro Preview

GPT-5.6 Terra and Gemini 3.1 Pro Preview cost the same on a blended 3:1 input:output rate ($4.50 per 1M tokens). Gemini 3.1 Pro Preview has the larger context window (1,048,576 vs 1,047,576 tokens).

Pricing verified

API pricing per 1M tokens

ModelInput / 1M tokensOutput / 1M tokensBlended (3:1 mix)
GPT-5.6 Terra$2.00$12.00$4.50
Gemini 3.1 Pro Preview$2.00$12.00$4.50

Rates from official OpenAI pricing and official Google pricing, checked 2026-08-11.

What a real workload costs

Example: one request with 10,000 input tokens and 2,000 output tokens, then that request at 100,000 runs per month.

ModelPer request (10K in / 2K out)Per month (100K requests)Monthly delta
GPT-5.6 Terra$0.044$4,400—
Gemini 3.1 Pro Preview$0.044$4,400—

Model your own prompt sizes and volumes in the token cost analyzer, or check caching savings with the prompt caching calculator.

Specs side by side

SpecGPT-5.6 TerraGemini 3.1 Pro Preview
ProviderOpenAIGoogle
Context window1,047,576 tokens1,048,576 tokens
Model classGeneral textReasoning
Tokenizero200k_base (exact, public)Proprietary (counts estimated)

Count tokens for each model on its own page: GPT-5.6 Terra token counter and Gemini 3.1 Pro Preview token counter. All OpenAI models are on the OpenAI Token Counter. All Google models are on the Gemini Token Counter.

FAQ

GPT-5.6 Terra vs Gemini 3.1 Pro Preview FAQ

Which is cheaper, GPT-5.6 Terra or Gemini 3.1 Pro Preview?

They currently cost the same blended rate. GPT-5.6 Terra is $2.00 in / $12.00 out per 1M tokens and Gemini 3.1 Pro Preview is $2.00 in / $12.00 out, checked 2026-08-11.

How much does a real request cost on GPT-5.6 Terra vs Gemini 3.1 Pro Preview?

A request with 10,000 input tokens and 2,000 output tokens costs about $0.044 on GPT-5.6 Terra and $0.044 on Gemini 3.1 Pro Preview. At 100,000 such requests per month that is $4,400 vs $4,400.

Which has the bigger context window, GPT-5.6 Terra or Gemini 3.1 Pro Preview?

Gemini 3.1 Pro Preview. It supports 1,048,576 tokens of context versus 1,047,576 tokens — roughly 786,000 English words in one request.

Do GPT-5.6 Terra and Gemini 3.1 Pro Preview count tokens the same way?

Not exactly. GPT-5.6 Terra uses the published o200k_base tokenizer and Gemini 3.1 Pro Preview uses a proprietary tokenizer (counts are estimates). The same prompt will tokenize differently, which shifts effective cost per word.