Models / Mistral AI /  / Ministral 3 14B Instruct 2512 API

Ministral 3 14B Instruct 2512 API

Frontier 14B multimodal model for high-quality assistants, analytics, and multilingual reasoning.

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Introducing Ministral 3 14B Instruct 2512

Ministral 3 14B Instruct is Mistral AI’s frontier 14B-class multimodal assistant, combining a 13.5B language core with a 0.4B vision encoder for unified text–image reasoning. With a 256K token context window and strong adherence to system prompts, it is built for long-horizon agents, complex chat experiences, and analytical copilots. Released under an Apache 2.0 license, Ministral 3 14B delivers advanced capabilities while remaining fully open and customizable for deep integration.

256K
Context Window
Long-horizon conversations, documents, and tool-call traces in a single pass.
14B
Frontier-Class Scale
Strong reasoning, coding, and multilingual performance in a compact frontier-tier model.
Vision
Multimodal IO
Joint understanding of documents, screenshots, and natural language queries for rich assistant experiences.
Key Capabilities
Multimodal Assistant: Joint text–image reasoning for chat, document analysis, dashboards, and visual debugging workflows.
Agentic Tool Use: Native function calling and structured outputs for long-running agents and automation pipelines.
Multilingual & Code: Broad language coverage and strong code handling for global products and technical copilots.
Long-Context Reasoning: Designed for retrieval-heavy, multi-step workflows that rely on stable behavior over very large prompts.

Ministral 3 14B Instruct 2512 API Usage

Endpoint

curl -X POST "https://api.together.xyz/v1/chat/completions" \
  -H "Authorization: Bearer $TOGETHER_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "mistralai/Ministral-3-14B-Instruct-2512",
    "messages": [
      {
        "role": "user",
        "content": "What are some fun things to do in New York?"
      }
    ]
}'
curl -X POST "https://api.together.xyz/v1/images/generations" \
  -H "Authorization: Bearer $TOGETHER_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "mistralai/Ministral-3-14B-Instruct-2512",
    "prompt": "Draw an anime style version of this image.",
    "width": 1024,
    "height": 768,
    "steps": 28,
    "n": 1,
    "response_format": "url",
    "image_url": "https://huggingface.co/datasets/patrickvonplaten/random_img/resolve/main/yosemite.png"
  }'
curl -X POST https://api.together.xyz/v1/chat/completions \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer $TOGETHER_API_KEY" \
  -d '{
    "model": "mistralai/Ministral-3-14B-Instruct-2512",
    "messages": [{
      "role": "user",
      "content": [
        {"type": "text", "text": "Describe what you see in this image."},
        {"type": "image_url", "image_url": {"url": "https://huggingface.co/datasets/patrickvonplaten/random_img/resolve/main/yosemite.png"}}
      ]
    }],
    "max_tokens": 512
  }'
curl -X POST https://api.together.xyz/v1/chat/completions \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer $TOGETHER_API_KEY" \
  -d '{
    "model": "mistralai/Ministral-3-14B-Instruct-2512",
    "messages": [{
      "role": "user",
      "content": "Given two binary strings `a` and `b`, return their sum as a binary string"
    }]
  }'
curl -X POST https://api.together.xyz/v1/rerank \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer $TOGETHER_API_KEY" \
  -d '{
    "model": "mistralai/Ministral-3-14B-Instruct-2512",
    "query": "What animals can I find near Peru?",
    "documents": [
      "The giant panda (Ailuropoda melanoleuca), also known as the panda bear or simply panda, is a bear species endemic to China.",
      "The llama is a domesticated South American camelid, widely used as a meat and pack animal by Andean cultures since the pre-Columbian era.",
      "The wild Bactrian camel (Camelus ferus) is an endangered species of camel endemic to Northwest China and southwestern Mongolia.",
      "The guanaco is a camelid native to South America, closely related to the llama. Guanacos are one of two wild South American camelids; the other species is the vicuña, which lives at higher elevations."
    ],
    "top_n": 2
  }'
curl -X POST https://api.together.xyz/v1/embeddings \
  -H "Authorization: Bearer $TOGETHER_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "input": "Our solar system orbits the Milky Way galaxy at about 515,000 mph.",
    "model": "mistralai/Ministral-3-14B-Instruct-2512"
  }'
curl -X POST https://api.together.xyz/v1/completions \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer $TOGETHER_API_KEY" \
  -d '{
    "model": "meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8",
    "prompt": "A horse is a horse",
    "max_tokens": 32,
    "temperature": 0.1,
    "safety_model": "mistralai/Ministral-3-14B-Instruct-2512"
  }'
curl --location 'https://api.together.ai/v1/audio/generations' \
  --header 'Content-Type: application/json' \
  --header 'Authorization: Bearer $TOGETHER_API_KEY' \
  --output speech.mp3 \
  --data '{
    "input": "Today is a wonderful day to build something people love!",
    "voice": "helpful woman",
    "response_format": "mp3",
    "sample_rate": 44100,
    "stream": false,
    "model": "mistralai/Ministral-3-14B-Instruct-2512"
  }'
curl -X POST "https://api.together.xyz/v1/audio/transcriptions" \
  -H "Authorization: Bearer $TOGETHER_API_KEY" \
  -F "model=mistralai/Ministral-3-14B-Instruct-2512" \
  -F "language=en" \
  -F "response_format=json" \
  -F "timestamp_granularities=segment"
curl --request POST \
  --url https://api.together.xyz/v2/videos \
  --header "Authorization: Bearer $TOGETHER_API_KEY" \
  --header "Content-Type: application/json" \
  --data '{
    "model": "mistralai/Ministral-3-14B-Instruct-2512",
    "prompt": "some penguins building a snowman"
  }'
curl --request POST \
  --url https://api.together.xyz/v2/videos \
  --header "Authorization: Bearer $TOGETHER_API_KEY" \
  --header "Content-Type: application/json" \
  --data '{
    "model": "mistralai/Ministral-3-14B-Instruct-2512",
    "frame_images": [{"input_image": "https://cdn.pixabay.com/photo/2020/05/20/08/27/cat-5195431_1280.jpg"}]
  }'

from together import Together

client = Together()

response = client.chat.completions.create(
  model="mistralai/Ministral-3-14B-Instruct-2512",
  messages=[
    {
      "role": "user",
      "content": "What are some fun things to do in New York?"
    }
  ]
)
print(response.choices[0].message.content)
from together import Together

client = Together()

imageCompletion = client.images.generate(
    model="mistralai/Ministral-3-14B-Instruct-2512",
    width=1024,
    height=768,
    steps=28,
    prompt="Draw an anime style version of this image.",
    image_url="https://huggingface.co/datasets/patrickvonplaten/random_img/resolve/main/yosemite.png",
)

print(imageCompletion.data[0].url)


from together import Together

client = Together()

response = client.chat.completions.create(
    model="mistralai/Ministral-3-14B-Instruct-2512",
    messages=[{
    	"role": "user",
      "content": [
        {"type": "text", "text": "Describe what you see in this image."},
        {"type": "image_url", "image_url": {"url": "https://huggingface.co/datasets/patrickvonplaten/random_img/resolve/main/yosemite.png"}}
      ]
    }]
)
print(response.choices[0].message.content)

from together import Together

client = Together()
response = client.chat.completions.create(
  model="mistralai/Ministral-3-14B-Instruct-2512",
  messages=[
  	{
	    "role": "user", 
      "content": "Given two binary strings `a` and `b`, return their sum as a binary string"
    }
 ],
)

print(response.choices[0].message.content)

from together import Together

client = Together()

query = "What animals can I find near Peru?"

documents = [
  "The giant panda (Ailuropoda melanoleuca), also known as the panda bear or simply panda, is a bear species endemic to China.",
  "The llama is a domesticated South American camelid, widely used as a meat and pack animal by Andean cultures since the pre-Columbian era.",
  "The wild Bactrian camel (Camelus ferus) is an endangered species of camel endemic to Northwest China and southwestern Mongolia.",
  "The guanaco is a camelid native to South America, closely related to the llama. Guanacos are one of two wild South American camelids; the other species is the vicuña, which lives at higher elevations.",
]

response = client.rerank.create(
  model="mistralai/Ministral-3-14B-Instruct-2512",
  query=query,
  documents=documents,
  top_n=2
)

for result in response.results:
    print(f"Relevance Score: {result.relevance_score}")

from together import Together

client = Together()

response = client.embeddings.create(
  model = "mistralai/Ministral-3-14B-Instruct-2512",
  input = "Our solar system orbits the Milky Way galaxy at about 515,000 mph"
)

from together import Together

client = Together()

response = client.completions.create(
  model="meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8",
  prompt="A horse is a horse",
  max_tokens=32,
  temperature=0.1,
  safety_model="mistralai/Ministral-3-14B-Instruct-2512",
)

print(response.choices[0].text)

from together import Together

client = Together()

speech_file_path = "speech.mp3"

response = client.audio.speech.create(
  model="mistralai/Ministral-3-14B-Instruct-2512",
  input="Today is a wonderful day to build something people love!",
  voice="helpful woman",
)
    
response.stream_to_file(speech_file_path)

from together import Together

client = Together()
response = client.audio.transcribe(
    model="mistralai/Ministral-3-14B-Instruct-2512",
    language="en",
    response_format="json",
    timestamp_granularities="segment"
)
print(response.text)
from together import Together

client = Together()

# Create a video generation job
job = client.videos.create(
    prompt="A serene sunset over the ocean with gentle waves",
    model="mistralai/Ministral-3-14B-Instruct-2512"
)
from together import Together

client = Together()

job = client.videos.create(
    model="mistralai/Ministral-3-14B-Instruct-2512",
    frame_images=[
        {
            "input_image": "https://cdn.pixabay.com/photo/2020/05/20/08/27/cat-5195431_1280.jpg",
        }
    ]
)
import Together from 'together-ai';
const together = new Together();

const completion = await together.chat.completions.create({
  model: 'mistralai/Ministral-3-14B-Instruct-2512',
  messages: [
    {
      role: 'user',
      content: 'What are some fun things to do in New York?'
     }
  ],
});

console.log(completion.choices[0].message.content);
import Together from "together-ai";

const together = new Together();

async function main() {
  const response = await together.images.create({
    model: "mistralai/Ministral-3-14B-Instruct-2512",
    width: 1024,
    height: 1024,
    steps: 28,
    prompt: "Draw an anime style version of this image.",
    image_url: "https://huggingface.co/datasets/patrickvonplaten/random_img/resolve/main/yosemite.png",
  });

  console.log(response.data[0].url);
}

main();

import Together from "together-ai";

const together = new Together();
const imageUrl = "https://huggingface.co/datasets/patrickvonplaten/random_img/resolve/main/yosemite.png";

async function main() {
  const response = await together.chat.completions.create({
    model: "mistralai/Ministral-3-14B-Instruct-2512",
    messages: [{
      role: "user",
      content: [
        { type: "text", text: "Describe what you see in this image." },
        { type: "image_url", image_url: { url: imageUrl } }
      ]
    }]
  });
  
  console.log(response.choices[0]?.message?.content);
}

main();

import Together from "together-ai";

const together = new Together();

async function main() {
  const response = await together.chat.completions.create({
    model: "mistralai/Ministral-3-14B-Instruct-2512",
    messages: [{
      role: "user",
      content: "Given two binary strings `a` and `b`, return their sum as a binary string"
    }]
  });
  
  console.log(response.choices[0]?.message?.content);
}

main();

import Together from "together-ai";

const together = new Together();

const query = "What animals can I find near Peru?";
const documents = [
  "The giant panda (Ailuropoda melanoleuca), also known as the panda bear or simply panda, is a bear species endemic to China.",
  "The llama is a domesticated South American camelid, widely used as a meat and pack animal by Andean cultures since the pre-Columbian era.",
  "The wild Bactrian camel (Camelus ferus) is an endangered species of camel endemic to Northwest China and southwestern Mongolia.",
  "The guanaco is a camelid native to South America, closely related to the llama. Guanacos are one of two wild South American camelids; the other species is the vicuña, which lives at higher elevations."
];

async function main() {
  const response = await together.rerank.create({
    model: "mistralai/Ministral-3-14B-Instruct-2512",
    query: query,
    documents: documents,
    top_n: 2
  });
  
  for (const result of response.results) {
    console.log(`Relevance Score: ${result.relevance_score}`);
  }
}

main();


import Together from "together-ai";

const together = new Together();

const response = await client.embeddings.create({
  model: 'mistralai/Ministral-3-14B-Instruct-2512',
  input: 'Our solar system orbits the Milky Way galaxy at about 515,000 mph',
});

import Together from "together-ai";

const together = new Together();

async function main() {
  const response = await together.completions.create({
    model: "meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8",
    prompt: "A horse is a horse",
    max_tokens: 32,
    temperature: 0.1,
    safety_model: "mistralai/Ministral-3-14B-Instruct-2512"
  });
  
  console.log(response.choices[0]?.text);
}

main();

import Together from 'together-ai';

const together = new Together();

async function generateAudio() {
   const res = await together.audio.create({
    input: 'Today is a wonderful day to build something people love!',
    voice: 'helpful woman',
    response_format: 'mp3',
    sample_rate: 44100,
    stream: false,
    model: 'mistralai/Ministral-3-14B-Instruct-2512',
  });

  if (res.body) {
    console.log(res.body);
    const nodeStream = Readable.from(res.body as ReadableStream);
    const fileStream = createWriteStream('./speech.mp3');

    nodeStream.pipe(fileStream);
  }
}

generateAudio();

import Together from "together-ai";

const together = new Together();

const response = await together.audio.transcriptions.create(
  model: "mistralai/Ministral-3-14B-Instruct-2512",
  language: "en",
  response_format: "json",
  timestamp_granularities: "segment"
});
console.log(response)
import Together from "together-ai";

const together = new Together();

async function main() {
  // Create a video generation job
  const job = await together.videos.create({
    prompt: "A serene sunset over the ocean with gentle waves",
    model: "mistralai/Ministral-3-14B-Instruct-2512"
  });
import Together from "together-ai";

const together = new Together();

const job = await together.videos.create({
  model: "mistralai/Ministral-3-14B-Instruct-2512",
  frame_images: [
    {
      input_image: "https://cdn.pixabay.com/photo/2020/05/20/08/27/cat-5195431_1280.jpg",
    }
  ]
});

How to use Ministral 3 14B Instruct 2512

Model details

Architecture overview:
• Dense 14B-class language model paired with a lightweight vision encoder, exposed as a single interface for text and images.
• 256K token context window designed for extended conversations, document analysis, and long-running tool-call traces.
• Instruction-tuned head focused on stable assistant behavior, schema-following, and controllable output formatting for agents and workflows.

Training and performance:
• Trained on diverse multilingual, code, and web-style data to cover a wide range of reasoning and analytic tasks.
• Instruct variant optimized for dialogue, tool use, and structured outputs rather than raw pretraining perplexity.
• Positioned to compete with much larger models on many assistant, coding, and reasoning tasks while keeping latency and cost more manageable.

Prompting Ministral 3 14B Instruct 2512

Applications & Use Cases

Assistants and agents:
• High-end multilingual assistants for support, operations, and knowledge work that require grounded, explainable responses.
• Internal copilots that coordinate retrieval, tools, and business logic to automate complex, multi-step workflows.
• Agentic systems that plan, call tools, and synthesize results into concise recommendations or actions.

Knowledge, content, and multimodal workflows:
• Long-document analysis, summarization, and synthesis across technical docs, contracts, product specs, and knowledge bases using the 256K context window.
• Multimodal understanding of screenshots, diagrams, and document snippets for debugging, troubleshooting, and guided workflows.
• High-quality content drafting, editing, and transformation across many languages, including structured reports, specifications, and templated outputs.

Looking for production scale? Deploy on a dedicated endpoint

Deploy Ministral 3 14B Instruct 2512 on a dedicated endpoint with custom hardware configuration, as many instances as you need, and auto-scaling.

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