Mistral AI
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Ministral 3 3B API

The Ministral 3 3B API: Mistral AI's smallest open-weight model, with vision, for fast, high-volume work, 70% below Mistral's-Listenpreis

Preis pro 1M Tokens70%Rabatt
Input
$0.03$0.10
Output
$0.03$0.10
Hol dir deinen API-KeyIm Playground ausprobieren
Model IDministral-3-3b
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-3-3b",
    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="")

Base URL https://api.zurelay.com/v1. Funktioniert mit jedem OpenAI SDK. Chat-API-Doku

Kontextfenster
128K Tokens
Reasoning
Keines
Input
Text, Image
Veröffentlicht
2. Dez. 2025
Status
Betriebsbereit

Preise

Ministral 3 3B API-Preise. Ein Bruchteil des Listenpreises.

Du zahlst aus Prepaid-Guthaben, ohne Abo. Lade ab $10 auf. Fehlgeschlagene Anfragen werden nie berechnet.

PreisZurelayMistral AI-Listenpreis
Input
pro 1M tokens
$0.03$0.10
Output
pro 1M tokens
$0.03$0.10

Ein Preis unabhängig von der Prompt-Länge, up to the full 128K context window. Streaming, Tool-Aufrufe und strukturierte Ausgaben kosten nichts extra.

Sparrechner

Stell mit den Reglern deinen monatlichen Verbrauch ein.

Eingabe-Token pro Monat50M
Ausgabe-Token pro Monat10M
Zurelay
$1.80
Mistral AI-Listenpreis
$6.00
Du sparst jeden Monat$4.20

$50.40 pro Jahr

Übersicht

Was ist Ministral 3 3B?

Ministral 3 3B is the smallest model in Mistral AI's Ministral 3 family, released on December 2, 2025: an open-weight model that reads text und images, made for fast, low-cost work such as classification, extraction, translation und image captions. The Zurelay Ministral 3 3B API serves its instruct version through one OpenAI-compatible endpoint with a 131,072-token context window, at 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 und 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 3B pairs a 3.4B-parameter language model with a 0.4B-parameter vision encoder, and Mistral says it fits in 8GB of GPU memory at FP8. On Zurelay the model ID is ministral-3-3b, and it kostet $0.03 per 1M input tokens and $0.03 pro 1M Output-Tokens.

Mistral built Ministral 3 for edge und local use, und points the 3B model at lightweight, real-time work: image captions, text classification, translation, data extraction and short content. 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 56.8 on WildBench, level with Qwen3-VL-4B-Instruct und ahead of Gemma 3 4B (49.1), und 0.830 on MATH, ahead of Gemma 3 4B (0.759) and behind Qwen3-VL-4B-Instruct (0.900). Qwen3-VL-4B-Instruct also leads it on Arena Hard, 0.438 against 0.305. 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 und while streaming, und 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 360 tokens a second and knew little about events after 2024, as small models tend to, so put the facts it needs in the prompt. You pay $0.03 per 1M input tokens and $0.03 per 1M output tokens against Mistral's list price of $0.10 and $0.10.

Stärken

Worin Ministral 3 3B glänzt. Und was Teams damit entwickeln.

01

Fast und very cheap

Über 360 tokens a second in our tests, bei $0.03 per 1M input tokens, for steps that run millions of times.

02

Liest Bilder

A 0.4B-parameter vision encoder reads photos, screenshots und scans next to your text, for captions und quick visual checks.

03

Tools und JSON

Funktionsaufrufe und JSON output that Mistral describes as native, for routing, extraction und small agent steps.

04

Offene Modellgewichte

Apache 2.0 weights auf Hugging Face, small enough for 8GB von GPU memory, so what you build on Zurelay carries over to a local copy later.

Anwendungsfälle

  • Klassifizierung und Routing

    Sort tickets, tag content und pick the next step in a pipeline, with JSON schema output for the code that follows.

  • Extraktion

    Pull fields from text, forms und screenshots into JSON bei a very low price per call.

  • Translation

    Quick translation between the languages Mistral lists, including English, French, Spanish, German, Chinese, Japanese und Arabic.

  • Image captions

    Short descriptions und alt text for photos und screenshots at volume.

Jetzt starten

Nutze Ministral 3 3B in drei Schritten.

Keine Warteliste und kein neues SDK. Wenn dein Code bereits mit OpenAI kommuniziert, funktioniert er auch mit Zurelay.

  1. 1

    Key erstellen

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

    Hol dir deinen API-Key
  2. 2

    Point your SDK bei Zurelay

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

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

    Use ministral-3-3b

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

    ministral-3-3b

Funktioniert mit den Tools, die du schon nutzt

Vergleich

Ähnliche Modelle. Alle mit demselben Schlüssel.

70%Rabatt

Ministral 3 14B

$0.06 / $0.06 pro 1M tokens

Pick Ministral 3 14B, the largest Ministral 3 model, for stronger answers: 0.551 against 0.305 on Arena Hard in Mistral's tests, bei twice the price per token.

Ministral 3 14B API
53%Rabatt

Qwen 3.8 Flash

$0.07 / $0.22 pro 1M tokens

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

Qwen 3.8 Flash API
90%Rabatt

DeepSeek V4.1 Flash

$0.03 / $0.12 pro 1M tokens

Pick DeepSeek V4.1 Flash for a 1M-token context und thinking on harder text and image tasks.

DeepSeek V4.1 Flash API

FAQ

Fragen zur Ministral 3 3B API.

Noch Fragen? Frag unser Team – wir antworten dir per E-Mail.

Was kostet die Ministral 3 3B API?

On Zurelay, ministral-3-3b costs $0.03 per 1M input tokens und $0.03 per 1M output tokens. Mistral's list price is $0.10 input und $0.10 output per 1M, so you save 70%. One rate applies at every prompt length, and failed requests are never billed.

Wie rufe ich the Ministral 3 3B API mit dem OpenAI SDK auf?

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

Was ist the Ministral 3 3B 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 und images und writes text.

Can Ministral 3 3B read Bilds or PDFs?

It reads Bilds: send them in image_url parts, as https links or base64 data URLs, und 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 3B: a request that includes one is turned away with a clear error before anything is billed.

Does Ministral 3 3B reason before it answers?

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

Does Ministral 3 3B support tool calling und 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, und tool_choice "none" works. Tool call ids must be at least 9 characters long, as the model's own und 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 3B or Ministral 3 14B?

Both read text und images, hold 131,072 tokens on Zurelay und call tools. 14B pairs a 13.5B-parameter language model with the same 0.4B vision encoder and scores higher in Mistral's tests (0.551 against 0.305 on Arena Hard, 68.5 against 56.8 on WildBench), at twice the price. 3B is faster, about 360 tokens a second against 170 in our tests, and suits simple, high-volume steps.

Is Ministral 3 3B open source?

Its weights are open under the Apache 2.0 license, which allows commercial use und changes. Mistral publishes base, instruct und reasoning versions on Hugging Face and says the 3B fits in 8GB 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 3B?

Yes. Requests for ministral-3-3b run on Mistral AI's Ministral 3 3B Instruct, und 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, und 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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