Source-tracked model comparison

How do GPT-5.6 Terra and Gemini 2.5 Pro costs compare for long-context analysis?

Compare verified pricing and model limits for large-context analysis with tiered pricing. The cost example uses a long-context research workload and does not assume equal model quality.

Direct cost answer: gpt-5.6-terra is estimated at $832.50 per month and Gemini 2.5 Pro at $441.25 for 150,000 input tokens, 5,000 output tokens, and 2,000 monthly requests. Gemini 2.5 Pro is $391.25 lower under these assumptions. This does not identify a quality winner.
low priorityobserveSources checked 2026-07-13 / 2026-07-12
Tracked facts

Pricing and model limits

Prices are USD per 1M tokens under each model's verified default profile.

Fieldgpt-5.6-terraGemini 2.5 Pro
ProviderOpenAIGoogle
API model IDgpt-5.6-terragemini-2.5-pro
Input / 1M$2.50$1.25
Cached input / 1M$0.25$0.125
Output / 1M$15.00$10.00
Context window1,050,000 tokens1,048,576 tokens
Maximum output128,000 tokens65,536 tokens
Accepted inputtext, imagetext, image, video, audio, pdf
Example workload

Long-context research cost scenario

150,000 input and 5,000 output tokens per request, 2,000 monthly requests, and 10% cached input.

OpenAI

gpt-5.6-terra

$832.50 / month
Input cost
$682.50
Output cost
$150.00
Per 1,000 calls
$416.25
Pricing profile
standard / short context
View model details
Google

Gemini 2.5 Pro

$441.25 / month
Input cost
$341.25
Output cost
$100.00
Per 1,000 calls
$220.63
Pricing profile
standard / short context
View model details

Cost result: Gemini 2.5 Pro is $391.25 lower per month for these assumptions. This is a price comparison, not a model-quality ranking.

StackLens assessment

Questions to answer before choosing

  • Which pricing threshold applies to the typical request?
  • Can retrieval reduce the amount of source material sent?
  • Which model meets the factuality and citation requirements in testing?
Workload caveat

What this estimate leaves out

Models whose tracked context window is below the scenario input are excluded from the compatible-model table.

Latency, reliability, output quality, retries, regional processing, and provider-specific tool charges can change the practical decision.