Bridge by Wekoya / Models / DeepSeek / DeepSeek-V3.1 API, priced in naira
DeepSeek-V3.1 API, priced in naira
In short: You can use DeepSeek-V3.1, a model by DeepSeek, from Nigeria through Bridge and pay in naira, with no dollar card. It costs ₦439 per million input tokens and ₦1,667 per million output tokens. Call it with the OpenAI SDK using the model ID deepseek-v3.1.
Updated
Price and limits
| DeepSeek-V3.1 | |
|---|---|
| Input, per million tokens | ₦439 |
| Output, per million tokens | ₦1,667 |
| Cached input, per million tokens | ₦228 |
| Writing to the cache, per million tokens | ₦439 |
| Context window | 163,840 tokens |
| Longest reply | 8,192 tokens |
| Reads pictures | No |
| Tool calling | Yes |
| Reasoning (thinks before it answers) | Yes |
| Model ID | deepseek-v3.1 |
Prices as of 8 November 2026. They are in naira and follow the exchange rate, so the live price may differ a little. A token is roughly three quarters of a word.
What a request costs
A request that sends 1,500 tokens (instructions, the conversation so far and a question) and gets 500 back (about 375 words) costs about ₦1.49 on 8 November 2026. A thousand of them cost about ₦1,492. When 1,000 of the input tokens are instructions that stay the same, prompt caching reads them at the cached rate and the request costs about ₦1.28.
Use DeepSeek-V3.1 from your code
Bridge speaks the OpenAI format, so the OpenAI SDK works as it is: set the base URL to https://wekoya-api.wekoya.tech/v1, use your Bridge key, and pass deepseek-v3.1 as the model. Create a key, then:
from openai import OpenAI
client = OpenAI(api_key="wk_live_...", base_url="https://wekoya-api.wekoya.tech/v1")
reply = client.chat.completions.create(
model="deepseek-v3.1",
messages=[{"role": "user", "content": "Hello"}],
)
print(reply.choices[0].message.content)Streaming works the same way, and so does tool calling. The quickstart has the same in JavaScript and curl, and the Responses API works too.
Other DeepSeek models on Bridge
| Model | Input / 1M | Output / 1M | Context |
|---|---|---|---|
| DeepSeek V4 Flash 0731 | ₦105 | ₦316 | 1,048,576 |
| DeepSeek V4.1 Flash 1017 | ₦172 | ₦516 | 1,048,576 |
| DeepSeek-V3.2 | ₦456 | ₦667 | 163,840 |
| DeepSeek-R1-0528 | ₦878 | ₦3,773 | 163,840 |
| DeepSeek V4 Pro 0813 | ₦2,282 | ₦4,563 | 1,048,576 |
Every DeepSeek model on Bridge, with what each can do.
Lower-priced models that can do the same things
These cost less per request than DeepSeek-V3.1 and can also call tools, reason and take at least 163,840 tokens of context. Quality differs from model to model, so test on your own examples first: AI tasks compares models on your cases and tells you whether a cheaper one is good enough.
| Model | Input / 1M | Output / 1M | Context |
|---|---|---|---|
| GPT-5.6 Luna | ₦297 | ₦1,782 | 1,050,000 |
| Nemotron 3 Nano Omni 30B A3B Reasoning | ₦351 | ₦1,404 | 262,144 |
| DeepSeek-V3.2 | ₦456 | ₦667 | 163,840 |
| NVIDIA Nemotron 3 Super 120B A12B | ₦263 | ₦1,141 | 262,144 |
Common questions
How much does DeepSeek-V3.1 cost in naira?
On Bridge, DeepSeek-V3.1 costs ₦439 per million input tokens and ₦1,667 per million output tokens, with cached input at ₦228 (as of 8 November 2026). A request that sends 1,500 tokens and gets 500 back costs about ₦1.49. There is no subscription and no minimum.
Can I use the DeepSeek-V3.1 API from Nigeria without a dollar card?
Yes. Create a free Bridge account, top up your naira balance by bank transfer to your own account number, and call DeepSeek-V3.1 with your Bridge key. A card works too, but it is not needed.
Does DeepSeek-V3.1 on Bridge work with the OpenAI SDK?
Yes. Use the OpenAI SDK or any OpenAI-compatible client with the base URL https://wekoya-api.wekoya.tech/v1 and the model ID deepseek-v3.1. Streaming works, and so does tool calling.
What is the context window of DeepSeek-V3.1?
163,840 tokens, about 122,880 words of instructions, conversation and documents together. It writes up to 8,192 tokens in one reply.
Can DeepSeek-V3.1 read pictures?
No. DeepSeek-V3.1 reads text only. For pictures, pick a model marked "Reads pictures" on the models page.