DeepSeek V4 Pro vs GPT-5.6 Luna

GPT-5.6 Luna is the cheaper of the two, at 1.2x less on a blended 3:1 input-to-output rate. DeepSeek V4 Pro runs $0.435 in / $0.87 out per 1M tokens; GPT-5.6 Luna runs $0.20 in / $1.20 out.

On the heaviest scenario below, that gap is $437.00 a month ($5,244 a year) for identical volume. Verified 2026-08-16.

Side by side

DeepSeek V4 Pro GPT-5.6 Luna
Provider DeepSeek OpenAI
Input per 1M tokens $0.435 $0.20
Output per 1M tokens $0.87 $1.20
Cached input per 1M $0.003625 $0.02
Batch discount Not offered Not offered
Output-to-input ratio 2.0x 6.0x
Blended per 1M (3:1) $0.544 $0.450

What each costs on the same workload

Rate cards are hard to compare directly because the input:output mix changes the answer. These four scenarios hold the workload fixed and vary only the model, with no caching or batch discount applied to either side.

Workload DeepSeek V4 Pro GPT-5.6 Luna Monthly difference Cheaper
Support chatbot
50,000 conversations/month at 3K input and 500 output tokens each
$87.00 $60.00 $27.00 GPT-5.6 Luna
RAG document search
200,000 queries/month at 6K retrieved-context input and 400 output tokens
$591.60 $336.00 $255.60 GPT-5.6 Luna
Coding agent
5,000 runs/month at 60K input and 8K output tokens per run
$165.30 $108.00 $57.30 GPT-5.6 Luna
Bulk classification
5,000,000 items/month at 400 input and 20 output tokens each
$957.00 $520.00 $437.00 GPT-5.6 Luna

Which should you actually pick?

There is no single winner here, and that is the useful finding. GPT-5.6 Luna has the cheaper input rate ($0.20 vs $0.435), while DeepSeek V4 Pro has the cheaper output rate ($0.87 vs $1.20). Prompt-heavy workloads such as retrieval-augmented search, long system prompts, and document analysis lean toward GPT-5.6 Luna. Generation-heavy workloads such as long-form writing, code generation, and agent loops that produce a lot of tokens lean toward DeepSeek V4 Pro.

Discounts can also flip the arithmetic. Prompt caching is the bigger lever of the two for anything that resends a stable prefix: see the prompt caching savings calculator.

DeepSeek V4 Pro vs GPT-5.6 Luna: common questions

Is DeepSeek V4 Pro or GPT-5.6 Luna cheaper?

GPT-5.6 Luna is cheaper overall, at 1.2x less on a blended 3:1 input-to-output rate ($0.450 vs $0.544 per 1M blended tokens). It is not a clean sweep though: GPT-5.6 Luna has the cheaper input rate while DeepSeek V4 Pro has the cheaper output rate, so a generation-heavy workload can flip the answer.

What is the price difference between DeepSeek V4 Pro and GPT-5.6 Luna on a real workload?

On the bulk classification scenario (5,000,000 items/month at 400 input and 20 output tokens each), DeepSeek V4 Pro costs $957.00 a month and GPT-5.6 Luna costs $520.00. That is a difference of $437.00 a month, or $5,244 a year, for the same volume of work.

Does DeepSeek V4 Pro or GPT-5.6 Luna have better discounts?

DeepSeek V4 Pro offers cached input at $0.003625. GPT-5.6 Luna offers cached input at $0.02. On cache-heavy or latency-tolerant workloads these can matter more than the headline rate.

Should I switch from DeepSeek V4 Pro to GPT-5.6 Luna?

Only if the cheaper model actually does the job. Price is the easy half of the decision; the hard half is whether output quality holds on your task. Run both against a sample of real traffic, then use the model switching savings calculator to put a number on the annual difference before committing.

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Go deeper

Rates last checked 2026-08-16 against DeepSeek Pricing and OpenAI Pricing. Cost scenarios are arithmetic on published list rates, not benchmarks: they say nothing about which model produces better output for your task.