Source-tracked model comparison

How do GPT-5.6 Terra and Claude Sonnet 4.6 costs compare for code review?

Compare verified pricing and model limits for code review and higher-value generation. The cost example uses a code review assistant workload and does not assume equal model quality.

Direct cost answer: gpt-5.6-terra is estimated at $611.25 per month and Claude Sonnet 4.6 at $679.50 for 15,000 input tokens, 1,800 output tokens, and 10,000 monthly requests. gpt-5.6-terra is $68.25 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-terraClaude Sonnet 4.6
ProviderOpenAIAnthropic
API model IDgpt-5.6-terraclaude-sonnet-4-6
Input / 1M$2.50$3.00
Cached input / 1M$0.25$0.30
Output / 1M$15.00$15.00
Context window1,050,000 tokens1,000,000 tokens
Maximum output128,000 tokens128,000 tokens
Accepted inputtext, imagetext, image
Example workload

Code review assistant cost scenario

15,000 input and 1,800 output tokens per request, 10,000 monthly requests, and 10% cached input.

OpenAI

gpt-5.6-terra

$611.25 / month
Input cost
$341.25
Output cost
$270.00
Per 1,000 calls
$61.13
Pricing profile
standard / short context
View model details
Anthropic

Claude Sonnet 4.6

$679.50 / month
Input cost
$409.50
Output cost
$270.00
Per 1,000 calls
$67.95
Pricing profile
standard
View model details

Cost result: gpt-5.6-terra is $68.25 lower per month for these assumptions. This is a price comparison, not a model-quality ranking.

StackLens assessment

Questions to answer before choosing

  • Which model catches the team's important review cases?
  • How often does a review require a follow-up call?
  • Will long prompts cross a tracked pricing threshold?
Workload caveat

What this estimate leaves out

This scenario does not claim equal review quality and excludes code indexing, sandbox, and repository-hosting costs.

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