Bridge by Wekoya / Models / Mistral / Ministral 14B 3.0 API, priced in naira
Ministral 14B 3.0 API, priced in naira
In short: You can use Ministral 14B 3.0, a model by Mistral, from Nigeria through Bridge and pay in naira, with no dollar card. It costs ₦351 per million input tokens and ₦351 per million output tokens. Call it with the OpenAI SDK using the model ID ministral-3-14b.
Updated
Price and limits
| Ministral 14B 3.0 | |
|---|---|
| Input, per million tokens | ₦351 |
| Output, per million tokens | ₦351 |
| Cached input, per million tokens | ₦351 |
| Writing to the cache, per million tokens | ₦351 |
| Context window | 128,000 tokens |
| Longest reply | 4,096 tokens |
| Reads pictures | Yes |
| Tool calling | Yes |
| Reasoning (thinks before it answers) | No |
| Model ID | ministral-3-14b |
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 ₦0.702 on 8 November 2026. A thousand of them cost about ₦702.
Use Ministral 14B 3.0 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 ministral-3-14b 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="ministral-3-14b",
messages=[{"role": "user", "content": "Hello"}],
)
print(reply.choices[0].message.content)Streaming works the same way, and so does tool calling. To send a picture, add it to the message as an image. The quickstart has the same in JavaScript and curl, and the Responses API works too.
Other Mistral models on Bridge
| Model | Input / 1M | Output / 1M | Context |
|---|---|---|---|
| Ministral 3 3B | ₦176 | ₦176 | 256,000 |
| Ministral 3 8B | ₦263 | ₦263 | 128,000 |
| Magistral Small 1.2 | ₦878 | ₦2,633 | 128,000 |
| Mistral Large 3 | ₦878 | ₦2,633 | 262,144 |
| Devstral 2 123B | ₦702 | ₦3,510 | 262,144 |
| Pixtral Large (25.02) | ₦3,510 | ₦10,530 | 128,000 |
Every Mistral model on Bridge, with what each can do.
Lower-priced models that can do the same things
These cost less per request than Ministral 14B 3.0 and can also read pictures, call tools and take at least 128,000 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 |
|---|---|---|---|
| Qwen3.8 Flash | ₦198 | ₦670 | 1,000,000 |
| Seed 2.0 Mini | ₦176 | ₦702 | 256,000 |
| MiMo-V2.6-Flash | ₦246 | ₦491 | 1,048,576 |
| GPT-6 Luna | ₦149 | ₦743 | 1,050,000 |
Common questions
How much does Ministral 14B 3.0 cost in naira?
On Bridge, Ministral 14B 3.0 costs ₦351 per million input tokens and ₦351 per million output tokens, with cached input at ₦351 (as of 8 November 2026). A request that sends 1,500 tokens and gets 500 back costs about ₦0.702. There is no subscription and no minimum.
Can I use the Ministral 14B 3.0 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 Ministral 14B 3.0 with your Bridge key. A card works too, but it is not needed.
Does Ministral 14B 3.0 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 ministral-3-14b. Streaming works, and so does tool calling.
What is the context window of Ministral 14B 3.0?
128,000 tokens, about 96,000 words of instructions, conversation and documents together. It writes up to 4,096 tokens in one reply.
Can Ministral 14B 3.0 read pictures?
Yes. Send a picture in the message as an image_url, by link or as base64, and Ministral 14B 3.0 reads it. Pictures are counted as input tokens.