Comparison · DeepSeek and OpenAI
DeepSeek V4 Pro 0813 vs GPT-5.4 Mini
Listed API prices of DeepSeek V4 Pro 0813 and GPT-5.4 Mini turned into the cost of the same three standard tasks, with speed from our own test requests in the United States and what each provider’s API documentation says about features that break on a switch. Output quality and answer length are not compared.
Calculated impact cost per task and per month
For an L2 task (deep analysis over a 50,000-token document, 3 steps), DeepSeek V4 Pro 0813 costs $0.222 and GPT-5.4 Mini $0.133 at the prices listed in the United States on , so DeepSeek V4 Pro 0813 is 67.1 % more than GPT-5.4 Mini, counting visible output only, without cache discounts or hidden reasoning.
| Task | DeepSeek V4 Pro 0813, per task | GPT-5.4 Mini, per task | DeepSeek V4 Pro 0813, per month | GPT-5.4 Mini, per month | DeepSeek V4 Pro 0813 vs GPT-5.4 Mini, per task |
|---|---|---|---|---|---|
| L1Micro-task (classification or strict JSON extraction) | $0.0028per L1 task | $0.0020per L1 task | $40.47per month | $29.57per month | +36.9 % |
| L2Deep analysis over a 50,000-token document | $0.222per L2 task | $0.133per L2 task | $3,237.70per month | $1,938.15per month | +67.1 % |
| L3Agentic coding loop, 15 steps | $1.77per L3 task | $1.03per L3 task | $25,872.66per month | $14,996.02per month | +72.5 % |
Calculated Per month: 20 tasks an hour around the clock, 730 hours.
Prices USD per 1M tokens
| Price | DeepSeek V4 Pro 0813 | GPT-5.4 Mini |
|---|---|---|
| Input, per 1M tokens | $1.32 | $0.750 |
| Output, per 1M tokens | $3.96 | $4.50 |
| Price from | Provider's price list · source page Published | Provider's price list · source page Published |
| Read | · the United States | · the United States |
| Context window | 1,048,576 tokens | 400,000 tokens |
What can I use it for? six common tasks, our data checks
Quality on your task: not measured by Measured Lab yet.
| Task | DeepSeek V4 Pro 0813 | GPT-5.4 Mini |
|---|---|---|
| Answer customer messages | Fits on price and context | Fits on price and context |
| Pull data from invoices and documents with strict JSON and page images | Not confirmed: reads text only, per the OpenRouter listing; strict JSON output partly, per DeepSeek’s documentation | Fits on price and context |
| Summarize documents and meetings | Fits on price and context | Fits on price and context |
| Translate content | Fits on price and context | Fits on price and context |
| Chat assistant on your website | Fits on price and context | Fits on price and context |
| Write and review code with tool calls | Fits on price and context | Fits on price and context |
| Tasks it fits | 5 of 6 | 6 of 6 |
Checks of our data for six common tasks: a published price, a context window and answer length for the task and, where the task needs them, strict JSON output, page images and tool calls; prices, cost a month and terms for each model on its model card. Compare models for your own task in the model picker.
Speed in the US Observed our test requests
In our test requests from the United States, the median time to the first answer token was 984 ms for DeepSeek V4 Pro 0813 (Direct API · DeepSeek) and 663 ms for GPT-5.4 Mini (Direct API · OpenAI).
| Model and route | Time to first answer token, median | Output speed, median | Answers |
|---|---|---|---|
| DeepSeek V4 Pro 0813Direct API · DeepSeek | 984 ms range 527 ms–1,480 ms | 75.5 tokens/s range 38.4 tokens/s–130 tokens/s | 115 answers on 23 dates |
| DeepSeek V4 Pro 0813Hosted by BytePlus | 1,865 ms range 1,309 ms–3,072 ms | 57.5 tokens/s range 45.0 tokens/s–74.0 tokens/s | 110 answers on 22 dates |
| GPT-5.4 MiniDirect API · OpenAI | 663 ms range 319 ms–30,568 ms | 156 tokens/s range 47.6 tokens/s–265 tokens/s | 120 answers on 23 dates |
The same short request to every model, sent from a measurement point in the United States; medians of successful answers on at least 2 different dates, latest on . How we measure
What breaks when you switch Published provider documentation
Moving from DeepSeek to OpenAI: every feature that DeepSeek’s documentation lists as supported is also listed as supported by OpenAI.
Moving from OpenAI to DeepSeek, 4 of the 5 features may not carry over, by each provider’s documentation:
- Strict JSON schemas — OpenAI: yes; DeepSeek: partly. Code that parses answers without checks starts failing where a provider promises only valid JSON, not your schema.
- Parallel tool calls — OpenAI: yes; DeepSeek: not stated. An agent built around several calls per turn gets one call per turn: more round trips, more input tokens, slower runs.
- Streamed tool arguments — OpenAI: yes; DeepSeek: not stated. An interface that shows arguments as they are written sees nothing until the whole call is ready.
- Cache covers tool definitions — OpenAI: yes; DeepSeek: not stated. Where the cache does not cover tool definitions, a long tool list is paid as fresh input on every request.
| Feature of the API | DeepSeek | OpenAI |
|---|---|---|
| Strict JSON schemas | Partly | Yes |
| Parallel tool calls | Not stated | Yes |
| Streamed tool arguments | Not stated | Yes |
| Reasoning with tools | Yes | Yes |
| Cache covers tool definitions | Not stated | Yes |
What each provider’s own API documentation says, read ; “not stated” is not the same as “no”. Quotes and sources: what breaks when you switch AI APIs.