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To use DeepSeek through an API, create an API key, choose an interface, and send requests to DeepSeek’s documented API base URL. For the OpenAI-compatible format, use https://api.deepseek.com; for the Anthropic-compatible format, use https://api.deepseek.com/anthropic. As of DeepSeek’s documentation reviewed on October 25, 2026, its model page lists deepseek-flash and deepseek-v4-pro. Check the live model list and pricing before deploying: model aliases, served versions, capabilities, and rates can change.
What do I need before making a DeepSeek API request?
You need a DeepSeek API key, a client that can send HTTP requests, a supported model name, and an API format. DeepSeek documents both OpenAI-compatible and Anthropic-compatible interfaces. The base URL determines which format you are using, so configure it to match the request structure and SDK rather than mixing the two.
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- OpenAI-compatible base URL: https://api.deepseek.com
- Anthropic-compatible base URL: https://api.deepseek.com/anthropic
- Model: DeepSeek’s documentation reviewed October 25, 2026 lists
deepseek-flashanddeepseek-v4-pro. The alias points to a served model version, which can change.
DeepSeek’s first-call guide provides curl and SDK examples for Python and Node.js. Use that guide for the current syntax and supported options for your selected format; avoid assuming that every parameter is shared across interfaces.
Which DeepSeek model name should I use?
Use the current model alias shown in DeepSeek’s live model list, not a version string copied from an old example. At the time of the October 25, 2026 documentation review, the listed aliases were deepseek-flash and deepseek-v4-pro.
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DeepSeek’s pricing page mapped deepseek-flash to DeepSeek-V4.1-Flash-1017 and deepseek-v4-pro to DeepSeek-V4-Pro-0813. DeepSeek’s October 17, 2026 changelog said V4.1 Flash had been upgraded to version 1017 and instructed callers to continue using the deepseek-flash alias. That distinction matters: callers use the alias in requests, while the underlying served version may be updated by DeepSeek.
Before building a production integration, check the live model list endpoint referenced in DeepSeek’s documentation and confirm the selected model is currently available to your account and supports the features you intend to use. The names and mappings above are time-sensitive, not a promise that the same versions will remain served.
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Configure your client with the OpenAI-compatible base URL and API key, then send a chat request with a model name and messages. A typical chat request includes a system message for instructions and a user message for the task; consult DeepSeek’s current first-call sample for the exact endpoint and SDK options.
Conceptually, the request has these parts:
- Authentication: Your API key is sent as a bearer credential. Keep it in a server-side secret or environment configuration rather than embedding it in an app distributed to users.
- Model: Set the current alias, such as
deepseek-flashordeepseek-v4-pro, after confirming it remains available. - Messages: Send the conversation as role-tagged messages. The official sample uses both a system message and a user message.
- Streaming choice: Enable streaming when you want output delivered incrementally; otherwise use a regular response.
For code, begin with DeepSeek’s official first-call page rather than copying an old snippet: DeepSeek API base URL. The base URL alone is not a substitute for the current guide’s full endpoint and request examples.
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Can I use DeepSeek with the Anthropic-compatible API?
Yes. DeepSeek documents an Anthropic-compatible interface at https://api.deepseek.com/anthropic. Configure an Anthropic-compatible client for that base URL and use the request schema and parameters documented for that format.
Compatibility is about the interface, not a guarantee that every provider-specific feature or parameter behaves identically across services. In particular, do not copy an OpenAI-format thinking parameter into an Anthropic-format call without checking DeepSeek’s current guide. Use the documentation for the selected interface as the authority for supported fields.
How does the Responses API work with DeepSeek?
DeepSeek documents a Responses API that can be called using an OpenAI SDK client configured with base_url="https://api.deepseek.com" and a responses.create call. The important integration detail is that DeepSeek’s Responses API is stateless: for a multi-turn conversation, your client must include the full conversation history in each request.
Do not assume that the server will remember earlier turns just because you reuse a client or make consecutive calls. Your application should retain the messages or other context it needs and send that history again with the next request. This increases the amount of input sent as a conversation grows, so consider how much history is relevant before passing it back on every turn.
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For streaming Responses API requests, DeepSeek describes semantic server-sent events. The stream can end with terminal events such as response.completed, response.incomplete, or response.failed. Handle terminal events explicitly: receiving streamed content is not, by itself, proof that the response completed successfully.
How do I control thinking and reasoning effort?
Thinking is enabled by default in the documented mode, but the control fields depend on the API format. Use the parameter names for the interface you selected and confirm the currently accepted effort values in DeepSeek’s guide.
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| Interface | Thinking control documented | Reasoning-effort control documented |
|---|---|---|
| Chat Completions | thinking enables or disables thinking |
reasoning_effort |
| Responses API | Consult the current Responses guide for its format-specific controls | reasoning.effort |
These fields are not interchangeable just because they describe related behavior. A request using the wrong field for its interface may not produce the intended setting. DeepSeek’s documentation can change the supported values and mappings, so verify them against the current guide rather than hard-coding an assumption from another format.
How much does the DeepSeek API cost?
DeepSeek bills by tokens. Its pricing table separates input cache hits, input cache misses, and output, and also lists peak and off-peak rates. The following are DeepSeek’s vendor-published deepseek-flash cache-miss input and output rates at the time checked; they are not independent measurements and may change.
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deepseek-flash charge type |
Peak rate per 1 million tokens | Off-peak rate per 1 million tokens |
|---|---|---|
| Input, cache miss | $0.30 | $0.15 |
| Output | $1.20 | $0.60 |
| Input, cache hit | See DeepSeek’s current pricing table | See DeepSeek’s current pricing table |
DeepSeek stated that off-peak rates were half of peak rates. It defined peak hours as 01:00–04:00 and 06:00–10:00 UTC, Monday through Friday, excluding Chinese public holidays. These rates and the schedule are vendor terms checked on October 25, 2026, not a permanent tariff. Check DeepSeek’s live pricing page before estimating spend or shipping a price estimate to customers.
Your bill depends on the number of input and output tokens and whether input is billed as a cache hit or cache miss. For the Responses API, resending full history in every multi-turn request means the amount of input can grow with the conversation. Keep that behavior in mind when estimating usage.
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Potentially. DeepSeek says context caching is enabled by default and can produce a cache hit when a later request fully matches a persisted prefix unit. The pricing page lists separate cache-hit rates, but a hit is not guaranteed: DeepSeek describes caching as best effort.
Because matching is prefix-based, repeated content at the start of requests is more relevant than content that merely appears somewhere in both prompts. A cache hit depends on the prefix matching the persisted unit; do not design a budget or promise savings on the assumption that every repeated prompt will be cached. Compare actual usage and the current cache-hit rate on DeepSeek’s pricing page.
What should I check when an API request does not work?
Start with the configuration choices most likely to cause a mismatch: key, base URL, format, model alias, and parameter names. If the request streams, also check whether your client handles the API’s streaming event format and terminal status.
- Authentication fails: Confirm the request is using the intended API key and that it is sent as a bearer credential. Never paste the key into a public issue or log.
- The request is rejected for its format: Check that the client’s request schema matches the base URL: OpenAI-compatible requests use
https://api.deepseek.com, while the Anthropic-compatible base URL ishttps://api.deepseek.com/anthropic. - The model is unavailable: Check DeepSeek’s live model list and replace a stale model name with a currently supported alias.
- A thinking setting appears ineffective: Confirm that you used the control for the chosen interface. Chat Completions uses
thinkingandreasoning_effort; Responses usesreasoning.effortfor effort. - A streamed result seems unfinished: Read the terminal event. DeepSeek documents
response.completed,response.incomplete, andresponse.failedfor Responses streaming. - A follow-up response lacks context: For the stateless Responses API, send the conversation history again with each multi-turn request.
Which integration should I choose?
Choose based on the client and conversation behavior your application needs. The OpenAI-compatible route is a straightforward fit for clients already built around that interface; the Anthropic-compatible route is available when your integration uses that format. The Responses API is another documented option, but requires you to manage history for multi-turn use.
| Need | Practical choice | Important consideration |
|---|---|---|
| Use an OpenAI-style client or Chat Completions flow | OpenAI-compatible base URL, https://api.deepseek.com |
Use the documented Chat Completions parameters for thinking and effort. |
| Use an Anthropic-compatible client | Anthropic-compatible base URL, https://api.deepseek.com/anthropic |
Follow the Anthropic-format request schema and its documented options. |
| Use the Responses API | OpenAI SDK configured for DeepSeek’s base URL and a responses.create call |
Send full history on every multi-turn request; handle semantic streaming terminal events if streaming. |
Whichever route you choose, pinning your application logic to a model alias does not freeze the underlying model version. Recheck the model list, pricing, and format-specific capabilities when updating or operating the integration.
Frequently Asked Questions
Can I call DeepSeek directly from a web browser?
Keep the API key on a server you control rather than in browser-delivered JavaScript: users can inspect client-side code and extract embedded credentials. Have your application server make the authenticated DeepSeek request and return only the result the browser needs.
Does DeepSeek remember earlier messages between API calls?
Not through the documented Responses API: it is stateless, so the caller is responsible for providing history. Do not infer persistent conversational memory from a reused SDK client.
Are DeepSeek API prices fixed in US dollars?
The rates quoted here are DeepSeek’s vendor-published USD rates as checked October 25, 2026, and the documentation warns that prices can change. Check the live pricing page before committing to a budget or quoting a rate.
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Does a repeated prompt always qualify for a cache hit?
No. DeepSeek characterizes context caching as best effort, and a hit depends on a matching persisted prefix unit. Repeated material later in a prompt is not enough to assume a hit.
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