Source-tracked model comparison

gpt-5.6-terra vs GPT-4o: which costs less for a practical API workload?

Compare verified pricing and model limits for routing within the GPT-5.6 family. The cost example uses a long-context research workload and does not assume equal model quality.

Direct cost answer: GPT-4o is estimated at $812.50 per month and gpt-5.6-terra at $832.50 for 150,000 input tokens, 5,000 output tokens, and 2,000 monthly requests. GPT-4o is $20.00 lower under these assumptions. This does not identify a quality winner.
low priorityobserveSources checked 2026-07-13 / 2026-07-13
Tracked facts

Pricing and model limits

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

FieldGPT-4ogpt-5.6-terra
ProviderOpenAIOpenAI
API model IDgpt-4ogpt-5.6-terra
Input / 1M$2.50$2.50
Cached input / 1M$1.25$0.25
Output / 1M$10.00$15.00
Context window128,000 tokens1,050,000 tokens
Maximum output16,384 tokens128,000 tokens
Accepted inputtext, imagetext, image
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-4o

$812.50 / month
Input cost
$712.50
Output cost
$100.00
Per 1,000 calls
$406.25
Pricing profile
standard
View model details
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

Cost result: GPT-4o is $20.00 lower per month for these assumptions. This is a price comparison, not a model-quality ranking.

StackLens assessment

Questions to answer before choosing

  • Which model meets the required quality threshold on representative inputs?
  • How do output length, retries, and caching change the measured cost?
  • Which provider and deployment path fit the team's operational requirements?
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.