Source-tracked model comparison

How do GPT-4o and Claude Sonnet 4.6 costs compare for developer assistance?

Compare verified pricing and model limits for developer assistance across providers. The cost example uses a developer assistant backend workload and does not assume equal model quality.

Direct cost answer: GPT-4o is estimated at $1,312.50 per month and Claude Sonnet 4.6 at $1,740.00 for 5,000 input tokens, 1,500 output tokens, and 50,000 monthly requests. GPT-4o is $427.50 lower under these assumptions. This does not identify a quality winner.
high priorityimproveSources 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-4oClaude Sonnet 4.6
ProviderOpenAIAnthropic
API model IDgpt-4oclaude-sonnet-4-6
Input / 1M$2.50$3.00
Cached input / 1M$1.25$0.30
Output / 1M$10.00$15.00
Context window128,000 tokens1,000,000 tokens
Maximum output16,384 tokens128,000 tokens
Accepted inputtext, imagetext, image
Example workload

Developer assistant backend cost scenario

5,000 input and 1,500 output tokens per request, 50,000 monthly requests, and 20% cached input.

OpenAI

GPT-4o

$1,312.50 / month
Input cost
$562.50
Output cost
$750.00
Per 1,000 calls
$26.25
Pricing profile
standard
View model details
Anthropic

Claude Sonnet 4.6

$1,740.00 / month
Input cost
$615.00
Output cost
$1,125.00
Per 1,000 calls
$34.80
Pricing profile
standard
View model details

Cost result: GPT-4o is $427.50 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 produces more accepted work on the team's repositories?
  • How much context is sent in a normal request?
  • Which integration path creates less rollout friction?
Workload caveat

What this estimate leaves out

The calculation does not compare coding quality and excludes indexing, execution sandboxes, and repository storage.

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