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PricesCompare → GPT-5.6 Terra vs Gemini 3.1 Pro

GPT-5.6 Terra vs Gemini 3.1 Pro: API cost compared

GPT-5.6 Terra lists at $1.000 in / $6.000 out per 1M tokens. Gemini 3.1 Pro lists at $2.000 in / $12.00. Sticker price only tells you so much — below is what each actually costs across eight production workloads.

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Cheaper on more workloads
GPT-5.6 Terra
wins 8 of 8
Blended rate gap
2.0x
at 3:1 in:out

Side by side

GPT-5.6 TerraGemini 3.1 Pro
ProviderOpenAIGoogle
Input per 1M$1.000$2.000
Output per 1M$6.000$12.00
Cached input per 1M$0.100not published
Context window400k1M
Blended per 1M (3:1)$2.250$4.500

Monthly cost by workload

Caching applied at each workload's typical hit rate. This is where the two models actually separate.

WorkloadGPT-5.6 TerraGemini 3.1 ProCheaperDifference
Customer support chatbot$146.40$390.00GPT-5.6 Terra$243.60 (62%)
RAG document Q&A$196.00$464.00GPT-5.6 Terra$268.00 (58%)
Coding agent$104.50$344.00GPT-5.6 Terra$239.50 (70%)
Bulk summarization$1,386$2,880GPT-5.6 Terra$1,494 (52%)
Structured data extraction$1,870$5,000GPT-5.6 Terra$3,130 (63%)
Long-form content generation$254.60$520.00GPT-5.6 Terra$265.40 (51%)
Email triage agent$432.50$1,360GPT-5.6 Terra$927.50 (68%)
Translation pipeline$1,645$3,330GPT-5.6 Terra$1,685 (51%)
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How to read this

GPT-5.6 Terra is cheaper on the majority of these workloads, but "majority" is not the decision. The output:input price ratio is 6.0 for GPT-5.6 Terra and 6.0 for Gemini 3.1 Pro. If your traffic is output-heavy — long-form drafting, translation — the model with the lower output price wins regardless of what the input price suggests. If you are input-heavy — RAG, bulk summarization, agents re-reading a codebase — the cached input rate matters more than either headline number.

Cost is also not the only axis. This site does not benchmark quality, latency, or rate limits, and a model that is 3x cheaper but needs two attempts per task is not cheaper. Use these numbers to size a bill, then validate on your own evals.

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