Question 1

Is DeepSeek V3 cheaper than GPT-5 nano?

Accepted Answer

Under an illustrative mix of 1M input and 200K output tokens, the stored listed rates make GPT-5 nano approximately 73% lower. This directional estimate excludes discounts, fees, taxes, availability, latency, and quality; verify current provider terms.

Question 2

What are the input and output token rates for GPT-5 nano and DeepSeek V3?

Accepted Answer

GPT-5 nano is listed at $0.05 per 1M input tokens and $0.40 per 1M output tokens. DeepSeek V3 is listed at $0.27 per 1M input tokens and $1.10 per 1M output tokens.

Question 3

How much can be saved by migrating between GPT-5 nano and DeepSeek V3?

Accepted Answer

Depending on your exact prompt length and output generation volume, switching to GPT-5 nano can reduce raw API token spend by approximately 73%. Use ModelPriceLab's cost diagnose tool to model your specific monthly workload.

Question 4

What should teams evaluate before switching from GPT-5 nano to DeepSeek V3?

Accepted Answer

Before migrating production workloads, engineering teams should evaluate output quality, structured JSON compliance, prompt sensitivity, latency percentiles, rate limits, and fallback strategies.

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GPT-5 nano vs DeepSeek V3

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