Source-tracked model comparison

DeepSeek V4 Pro vs GPT-4o Mini: how do structured-extraction API costs compare?

Compare verified pricing and model limits for cost-aware structured extraction across DeepSeek and OpenAI. The cost example uses a structured data extraction workload and does not assume equal model quality.

Direct cost answer: deepseek-v4-pro is estimated at $174.36 per month and GPT-4o mini at $82.50 for 4,000 input tokens, 500 output tokens, and 100,000 monthly requests. GPT-4o mini is $91.86 lower under these assumptions. This does not identify a quality winner.
Current provider alternativesStructured data extractionSources checked 2026-07-12 / 2026-07-13
Tracked facts

Pricing and model limits

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

Fielddeepseek-v4-proGPT-4o mini
ProviderDeepSeekOpenAI
API model IDdeepseek-v4-progpt-4o-mini
Input / 1M$0.435$0.15
Cached input / 1M$0.0036$0.075
Output / 1M$0.87$0.60
Context window1,000,000 tokens128,000 tokens
Maximum output384,000 tokens16,384 tokens
Accepted inputtexttext, image
Example workload

Structured data extraction cost scenario

4,000 input and 500 output tokens per request, 100,000 monthly requests, and 25% cached input.

DeepSeek

deepseek-v4-pro

$174.36 / month
Input cost
$130.86
Output cost
$43.50
Per 1,000 calls
$1.7436
Pricing profile
standard / cache miss
View model details
OpenAI

GPT-4o mini

$82.50 / month
Input cost
$52.50
Output cost
$30.00
Per 1,000 calls
$0.825
Pricing profile
standard
View model details

Cost result: GPT-4o mini is $91.86 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 fewer invalid structured outputs?
  • How does cache behavior change DeepSeek input cost?
  • Do deployment requirements favor either provider?
Workload caveat

What this estimate leaves out

Document parsing, OCR, validation infrastructure, and failed-record handling are outside this token estimate.

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