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Ministral 3 14B API

Harga resmi The Ministral 3 14B API: the largest Ministral 3 model, with vision dan tool calling, 70% below Mistral's

Harga per 1M token70%lebih murah
Input
$0.06$0.20
Output
$0.06$0.20
Dapatkan kunci API AndaCoba di playground
ID modelministral-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 dasar https://api.zurelay.com/v1. Kompatibel dengan semua SDK OpenAI. Dokumentasi API chat

Jendela konteks
128K tokens
Penalaran
Tidak ada
Input
Text, Image
Dirilis
2 Des 2025
Status
Beroperasi

Harga

Harga API Ministral 3 14B. Jauh di bawah harga resmi.

Bayar sesuai pemakaian dari saldo prabayar, tanpa langganan. Isi saldo mulai $10. Permintaan yang gagal tidak pernah dikenakan biaya.

TarifZurelayHarga resmi Mistral AI
Input
per 1M tokens
$0.06$0.20
Output
per 1M tokens
$0.06$0.20

Satu tarif untuk semua panjang prompt, up to the full 128K context window. Streaming, pemanggilan tool, dan output terstruktur tanpa biaya tambahan.

Kalkulator penghematan

Geser slider sesuai pemakaian bulanan Anda.

Token input per bulan50M
Token output per bulan10M
Zurelay
$3.60
Harga resmi Mistral AI
$12.00
Penghematan Anda per bulan$8.40

$100.80 per tahun

Ringkasan

Apa itu 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 dan 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, untuk 70% below Mistral's list price.

Biaya Mistral AI released the Ministral 3 family on December 2, 2025, alongside Mistral Large 3, in three sizes: 3B, 8B dan 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 adalah $0.06 per 1M input tokens and $0.06 per 1M token output.

Mistral built Ministral 3 for edge dan local use, dan 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 dan 0.904 on MATH, ahead of Qwen3 14B without thinking (0.427, 65.1 dan 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 dan while streaming, dan 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.

Keunggulan

Keunggulan Ministral 3 14B. Dan apa yang dibangun tim dengannya.

01

Strong for its size

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

02

Membaca gambar

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

03

Alat dan JSON

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

04

Bobot terbuka

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

Contoh penggunaan

  • Assistants dan chat

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

  • Agent steps

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

  • Gambar Extraction from text and

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

  • Multilingual work

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

Mulai

Panggil Ministral 3 14B dalam tiga langkah.

Tanpa daftar tunggu dan tanpa SDK baru. Jika kode Anda sudah terhubung ke OpenAI, kode itu juga bisa terhubung ke Zurelay.

  1. 1

    Buat kunci

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

    Dapatkan kunci API Anda
  2. 2

    Point your SDK untuk 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 dan usage reporting work as you expect.

    ministral-3-14b

Kompatibel dengan tool yang sudah Anda gunakan

Bandingkan

Model serupa. Semua dengan satu kunci.

70%lebih murah

Ministral 3 3B

$0.03 / $0.03 per 1M token

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

API Ministral 3 3B
53%lebih murah

Qwen 3.8 Flash

$0.07 / $0.22 per 1M token

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

API Qwen 3.8 Flash
61%lebih murah

Gemini 3.1 Flash-Lite

$0.10 / $0.59 per 1M token

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

API Gemini 3.1 Flash-Lite

Tanya jawab

Pertanyaan seputar API Ministral 3 14B.

Ada pertanyaan lain? Tanyakan kepada tim kami dan kami akan menjawab lewat email.

Berapa biaya API Ministral 3 14B?

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

Bagaimana cara memanggil the Ministral 3 14B API dengan SDK OpenAI?

Install the official openai package, set base_url to https://api.zurelay.com/v1 dan 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 dan ministral-14b. Mistral recommends a temperature of 0.1 or lower for production work.

Apa itu 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 dan images dan writes text.

Can Ministral 3 14B read gambars or PDFs?

It reads gambars: send them in image_url parts, as https links or base64 data URLs, dan 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 dan there are no reasoning tokens hingga 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 dan 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, dan tool_choice "none" works. Tool call ids must be at least 9 characters long, as the model's own dan 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 dan images, hold 131,072 tokens on Zurelay dan 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 dan changes. Mistral publishes base, instruct dan 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, dan 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, dan 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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