DeepSeek API Pricing Calculator
Estimate Your DeepSeek API Costs Instantly
Compare DeepSeek V4 Flash, V4 Pro, and competitor model pricing. Adjust input/output token counts and cache hit rate assumptions to see real cost projections.
How to Estimate Monthly Usage
If you do not already have billing exports, start from product traffic: requests per day, average prompt size, average response length, and expected cache reuse.
1. Estimate request volume
Count how many requests your app will send in a normal day, then multiply by 30. Separate peak campaigns from baseline traffic.
2. Estimate prompt and response size
Use a few representative prompts to approximate average input and output tokens. For rough planning, consistency matters more than absolute precision.
3. Add a cache assumption
If your system prompt and context are reused heavily, model a higher hit rate. If every request is unique, start closer to 0% and treat savings as upside.
How the Billing Model Works
Uncached input tokens
These are charged at the model's standard input rate. Large prompts dominate cost when the cache hit rate is low.
Cached input tokens
When the prefix matches a previous request, DeepSeek charges the reduced cache-hit price instead of the full input rate.
Output tokens
Generated tokens are billed separately and can become the main cost driver in agentic or reasoning-heavy workflows.
How to Read the Result
Use Flash for high-volume routine work
If the workload is repetitive and latency-sensitive, DeepSeek V4 Flash usually sets the floor for cost planning.
Use Pro when quality offsets the delta
The real question is not whether Pro is more expensive, but whether it cuts retries, human review, or downstream errors enough to justify the gap.
Compare competitors with your actual mix
A model that looks expensive on list price can still make sense for narrow tasks. Re-run the calculator with your own token mix before locking the stack.
DeepSeek API 价格计算器
即刻估算你的 DeepSeek API 成本
对比 DeepSeek V4 Flash、V4 Pro 及竞品模型价格。调整输入/输出 Token 数量和缓存命中率假设,查看真实的成本预估。
如何估算月用量
如果你手头还没有账单导出,可以先从产品流量倒推:每天请求数、平均 Prompt 长度、平均回复长度,以及预期缓存复用率。
1. 先估算请求量
统计应用在正常一天会发出多少请求,再乘以 30。把活动高峰和日常基线拆开估算更靠谱。
2. 再估算输入 / 输出 Token
挑几组有代表性的 Prompt,估算平均输入和输出 Token。做预算时,稳定的口径往往比极致精确更重要。
3. 最后补上缓存假设
如果系统提示词和上下文复用很高,就用更高的命中率建模;如果每次请求都很独特,就先按接近 0% 估算,把缓存收益当成上行空间。
计费模型怎么理解
未命中的输入 Token
这部分按模型标准输入价计费。当缓存命中率较低时,大 Prompt 往往是总成本的主导项。
命中的缓存输入 Token
当前缀命中历史请求时,DeepSeek 会按更低的缓存命中价格计费,而不是全额输入价格。
输出 Token
模型生成的输出会单独计费。在 Agent 或深度推理场景里,输出成本本身也可能成为主要开销。
如何解读计算结果
高频常规任务优先看 Flash
如果工作负载重复度高、又对延迟敏感,DeepSeek V4 Flash 往往是成本规划的基准下限。
只有质量收益覆盖价差时再上 Pro
关键不在于 Pro 是否更贵,而在于它是否能减少重试、人审和下游错误,从而抵掉这部分价差。
竞品比较要带入你的真实流量结构
列表价格看起来贵的模型,放到特定窄任务里仍可能合理。定栈前请用你自己的 Token 结构再跑一遍计算器。