Mistral Large

Mistral AI
Text & Chat

Mistral's flagship model. Strong reasoning, multilingual, and coding capabilities.

Try Mistral Large

0.7

Sign in to generate — 50 free credits on sign-up

Examples

See what Mistral Large can generate

Multilingual Writing

Write a short product description for a smartwatch in English, then translate it to French and German

English: The AuraFit Pro tracks your heart rate, sleep, and workouts with medical-grade accuracy. Its always-on AMOLED display and 7-day battery life keep you connected without compromise. French: L'AuraFit Pro suit votre fréquence cardiaque, votre sommeil et vos entraînements avec une précision de qualité médicale. Son écran AMOLED toujours actif et son autonomie de 7 jours vous gardent connecté sans compromis. Deutsch: Die AuraFit Pro überwacht Herzfrequenz, Schlaf und Training mit medizinischer Präzision. Das Always-on-AMOLED-Display und die 7-Tage-Akkulaufzeit halten Sie ohne Kompromisse verbunden.

Technical Documentation

Write a brief API documentation entry for a POST /users endpoint that creates a new user

## POST /users Creates a new user account. **Request Body:** ```json { "email": "string (required)", "name": "string (required)", "password": "string (required, min 8 chars)" } ``` **Response 201:** ```json { "id": "uuid", "email": "string", "name": "string", "createdAt": "ISO 8601" } ``` **Errors:** 400 (validation failed), 409 (email already exists), 500 (internal error). Rate limit: 10 requests per minute per IP.

Pricing

Price per Generation
Per generationFree

API Integration

Use our OpenAI-compatible API to integrate Mistral Large into your application.

Install
npm install railwail
JavaScript / TypeScript
import railwail from "railwail";

const rw = railwail("YOUR_API_KEY");

// Simple — just pass a string
const reply = await rw.run("mistral-large", "Hello! What can you do?");
console.log(reply);

// With message history
const reply2 = await rw.run("mistral-large", [
  { role: "system", content: "You are a helpful assistant." },
  { role: "user", content: "Explain quantum computing simply." },
]);
console.log(reply2);

// Full response with usage info
const res = await rw.chat("mistral-large", [
  { role: "user", content: "Hello!" },
], { temperature: 0.7, max_tokens: 500 });
console.log(res.choices[0].message.content);
console.log(res.usage);
Specifications
Context window
128,000 tokens
Max output
8,192 tokens
Avg. latency
2.5s
Developer
Mistral AI
Category
Text & Chat
Tags
multilingual
coding

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