Mistral AI
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Ministral 3 14B API

Precio de lista de The Ministral 3 14B API: the largest Ministral 3 model, with vision y tool calling, 70% below Mistral's

Precio por 1M de tokens70%off
Entrada
$0.06$0.20
Salida
$0.06$0.20
Obtén tu clave de APIPruébalo en el playground
ID del modeloministral-3-14b
chat.py
from openai import OpenAI
client = OpenAI(
    base_url="https://api.zurelay.com/v1",
    api_key="YOUR_ZURELAY_KEY",
)
stream = client.chat.completions.create(
    model="ministral-3-14b",
    messages=[{"role": "user", "content": "Explain quicksort in two sentences."}],
    stream=True,
)
for chunk in stream:
    if chunk.choices:
        print(chunk.choices[0].delta.content or "", end="")

URL base https://api.zurelay.com/v1. Funciona con cualquier OpenAI SDK. Documentación de la API de chat

Ventana de contexto
128K tokens
Razonamiento
Ninguno
Entrada
Text, Image
Lanzamiento
2 dic 2025
Estado
Operativo

Precios

Precios de la API de Ministral 3 14B. Una fracción del precio de lista.

Paga según el consumo desde un saldo prepago, sin suscripción. Recarga desde $10. Las solicitudes fallidas nunca se cobran.

TarifaZurelayMistral AI de lista
Entrada
por 1M de tokens
$0.06$0.20
Salida
por 1M de tokens
$0.06$0.20

Una sola tarifa para cualquier longitud de prompt, up to the full 128K context window. El streaming, las llamadas a herramientas y las salidas estructuradas no cuestan nada extra.

Calculadora de ahorro

Mueve los deslizadores según tu uso mensual.

Tokens de entrada al mes50M
Tokens de salida al mes10M
Zurelay
$3.60
Precio de lista de Mistral AI
$12.00
Ahorras cada mes$8.40

$100.80 al año

Resumen

¿Qué es Ministral 3 14B?

Ministral 3 14B is the largest model in Mistral AI's Ministral 3 family, released on December 2, 2025: an open-weight model that reads text y images and, by Mistral's account, performs comparably to its larger Mistral Small 3.2 24B. The Zurelay Ministral 3 14B API serves its instruct version through one OpenAI-compatible endpoint with a 131,072-token context window, a 70% below Mistral's list price.

Mistral AI released the Ministral 3 family on December 2, 2025, alongside Mistral Large 3, in three sizes: 3B, 8B y 14B. Each size comes as a base, an instruct and a reasoning model, all with image understanding and all under the Apache 2.0 license, with the weights on Hugging Face. Ministral 3 14B pairs a 13.5B-parameter language model with a 0.4B-parameter vision encoder, and Mistral says it fits in 24GB of GPU memory at FP8. On Zurelay the model ID is ministral-3-14b, and it cuesta $0.06 per 1M input tokens and $0.06 por 1M de tokens de salida.

Mistral built Ministral 3 for edge y local use, y points the 14B model at private chat and assistant deployments on limited hardware, local agents and fine-tuning. It handles dozens of languages, including English, French, Spanish, German, Italian, Portuguese, Dutch, Chinese, Japanese, Korean and Arabic. Mistral says its Ministral instruct models often write an order of magnitude fewer tokens than comparable models.

On Mistral's model card the instruct model scores 0.551 on Arena Hard, 68.5 on WildBench y 0.904 on MATH, ahead of Qwen3 14B without thinking (0.427, 65.1 y 0.870) and Gemma 3 12B (0.436, 63.2 and 0.854). On MM MTBench, a multimodal chat test, it scores 8.49 against 6.70 for Gemma 3 12B. These are Mistral's numbers, not independent ones.

The instruct model answers directly without reasoning first, so reasoning_effort has no effect. It calls tools, several at once y while streaming, y returns JSON for json_object or json_schema in response_format. Mistral lists a 256K context window on its own API; on Zurelay a request holds up to 131,072 tokens. In our tests it wrote about 170 tokens a second and knew little about events after 2024, so put the facts it needs in the prompt. You pay $0.06 per 1M input tokens and $0.06 per 1M output tokens against Mistral's list price of $0.20 and $0.20.

Puntos fuertes

Dónde destaca Ministral 3 14B. Y qué construyen los equipos con él.

01

Strong for its size

0.551 on Arena Hard y 68.5 on WildBench in Mistral's tests, ahead of Qwen3 14B y Gemma 3 12B, and comparable to Mistral Small 3.2 24B by Mistral's account.

02

Lee imágenes

8.49 en MM MTBench in Mistral's tests. Send screenshots, charts y photos next to your text.

03

Herramientas y JSON

Calls several tools at once, also while streaming, y follows a JSON schema, for agent steps y extraction.

04

Pesos abiertos

Apache 2.0 weights on Hugging Face that fit in 24GB de GPU memory a FP8, so what you build on Zurelay carries over to a self-hosted copy later.

Casos de uso

  • Assistants y chat

    Customer-facing chat y internal assistants that need good everyday answers a a very low price per token.

  • Agent steps

    Tool-calling steps such as looking things up, filling forms y choosing the next action, with JSON for the code that follows.

  • Extraction from text and imágenes

    Pull fields from emails, documents y screenshots into a JSON schema.

  • Multilingual work

    Translate, summarize y answer in the languages Mistral lists, from French y German to Chinese, Japanese and Arabic.

Comenzar

Llama a Ministral 3 14B en tres pasos.

Sin listas de espera y sin SDK nuevo. Si tu código ya habla con OpenAI, ya habla con Zurelay.

  1. 1

    Crear una clave

    Sign up, add credit y create an API key. Set a monthly budget or a rate limit per key if you like.

    Obtén tu clave de API
  2. 2

    Point your SDK a Zurelay

    Change the base URL. Everything else in your code stays the same.

    https://api.zurelay.com/v1
  3. 3

    Use ministral-3-14b

    Send chat completions as usual. Streaming, tool calls y usage reporting work as you expect.

    ministral-3-14b

Funciona con las herramientas que ya usas

Comparar

Modelos similares. Todos con la misma clave.

70%off

Ministral 3 3B

$0.03 / $0.03 por 1M tokens

Pick Ministral 3 3B for the simplest, highest-volume steps a half the price per token, about twice as fast in our tests.

API de Ministral 3 3B
53%off

Qwen 3.8 Flash

$0.07 / $0.22 por 1M tokens

Pick Qwen 3.8 Flash for a 1M-token context, video input y a thinking mode when a task needs more than a small model.

API de Qwen 3.8 Flash
61%off

Gemini 3.1 Flash-Lite

$0.10 / $0.59 por 1M tokens

Pick Gemini 3.1 Flash-Lite for Google's low-cost model with a 1M-token context y audio, video and PDF input.

API de Gemini 3.1 Flash-Lite

Preguntas frecuentes

Preguntas sobre la API de Ministral 3 14B.

¿Algo más? Pregunta a nuestro equipo y te responderemos por correo.

¿Cuánto cuesta la API de Ministral 3 14B?

On Zurelay, ministral-3-14b costs $0.06 per 1M input tokens y $0.06 per 1M output tokens. Mistral's list price is $0.20 input y $0.20 output per 1M, so you save 70%. One rate applies at every prompt length, and failed requests are never billed.

¿Cómo llamo a the Ministral 3 14B API con el SDK de OpenAI?

Install the official openai package, set base_url to https://api.zurelay.com/v1 y use your Zurelay API key. Then send a Chat Completions request with model set to "ministral-3-14b". Zurelay also accepts ministral-3-14b-instruct, mistralai/ministral-3-14b y ministral-14b. Mistral recommends a temperature of 0.1 or lower for production work.

¿Qué es the Ministral 3 14B context window?

On Zurelay a request holds up to 131,072 tokens. Mistral lists a 256K window on its own API. The model reads text y images y writes text.

Can Ministral 3 14B read imagenns or PDFs?

It reads imagens: send them in image_url parts, as https links or base64 data URLs, y they count as input tokens. Mistral suggests images close to square, with very wide or thin ones cropped. Zurelay doesn't take PDFs, audio or video for Ministral 3 14B: a request that includes one is turned away with a clear error before anything is billed.

Does Ministral 3 14B reason before it answers?

No. Zurelay serves the instruct model, which answers directly, so reasoning_effort has no effect y there are no reasoning tokens a pay for. Mistral also publishes a separate Ministral 3 14B Reasoning model, which Zurelay doesn't serve. For answers with thinking, use Qwen 3.8 Flash or DeepSeek V4.1 Flash.

Does Ministral 3 14B support tool calling y JSON output?

Yes. Pass tools as you would to any OpenAI model; it can call several at once, also while streaming. A tool forced by name is called, y tool_choice "none" works. Tool call ids must be at least 9 characters long, as the model's own y OpenAI's are. For JSON, send response_format with json_object or json_schema and the answer comes back as JSON.

Should I use Ministral 3 14B or Ministral 3 3B?

Both read text y images, hold 131,072 tokens on Zurelay y call tools. 14B is the stronger model, with a 13.5B-parameter language model against 3.4B, and scores higher in Mistral's tests: 0.551 against 0.305 on Arena Hard and 68.5 against 56.8 on WildBench. 3B costs half as much and was about twice as fast in our tests, so it suits the simplest, highest-volume steps.

Is Ministral 3 14B open source?

Its weights are open under the Apache 2.0 license, which allows commercial use y changes. Mistral publishes base, instruct y reasoning versions on Hugging Face and says the 14B fits in 24GB of GPU memory at FP8. The API is the quick way to use it without running your own hardware.

Is this the real Ministral 3 14B?

Yes. Requests for ministral-3-14b run on Mistral AI's Ministral 3 14B Instruct, y Zurelay doesn't swap in a different model. Only smart routing, which you turn on yourself, can answer with a close alternative when the model is down, y the x-zurelay-model header names the model that answered. Responses are sampled, so wording varies between runs. Zurelay is independent and is not affiliated with or endorsed by Mistral AI.

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