DeepSeek V3.2 costs $0.28 per million input tokens. Claude Sonnet 4.6 costs $3.00. GPT-5 costs $2.50. That’s an 89–93% price gap for models that score within a few percentage points of each other on most standard benchmarks. Whether that gap translates into real savings — or a compliance disaster — depends on your workload.
Pricing Breakdown: DeepSeek V3.2 vs Claude Sonnet 4.6 vs GPT-5 DeepSeek V3.2 is the cheapest frontier-class LLM available via public API in 2026, priced at $0.14–$0.28 per million input tokens and $0.42 per million output tokens. Claude Sonnet 4.6 runs $3.00 per million input and $15.00 per million output — more than 10× more expensive on output alone. GPT-5 sits between them at $2.50 input and $10–$15 output per million tokens. DeepSeek also offers a 90% cache discount on repeated context, making high-volume workloads with shared system prompts nearly free. For a developer running 10 million tokens per month in a document-summarization pipeline, DeepSeek costs roughly $420 in output fees; the same job costs $150,000 via Claude Sonnet 4.6 at full output rates. That’s not a rounding error — it’s a budget decision. The price gap exists because DeepSeek’s architecture uses DSA (Differential Sparse Attention), reducing computational complexity from O(L²) to O(Lk) and enabling 128K context windows at substantially lower inference cost. The takeaway: if you are not considering DeepSeek for cost-sensitive workloads, you are leaving significant money on the table.
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