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MistralAI ยท Chat / LLM ยท 7.3B Parameters ยท 32K ContextQubrid Playground License HuggingFaceStreaming Instruction Following Code Chat

Overview

Mistral 7B Instruct v0.3 is a 7.3B parameter language model celebrated for its efficiency, outperforming larger models on many benchmarks. The v0.3 instruct version is specifically fine-tuned for chat and instruction-following tasks โ€” delivering fast, high-quality responses with a remarkably low memory footprint. Whether youโ€™re building customer-facing assistants, developer tooling, or content pipelines, Mistral 7B v0.3 offers an outstanding performance-to-cost ratio.
๐ŸŽ๏ธ Fast inference. Low cost. High accuracy. โ€” Get started on the Qubrid AI Serverless API for just $0.21 / 1M input tokens.

Model Specifications

FieldDetails
Model IDmistralai/Mistral-7B-Instruct-v0.3
ProviderMistralAI
KindChat / LLM
Parameters7.3B
Context Length32,768 Tokens
MoENo
LicenseApache 2.0
Function CallingNot Supported
Image SupportN/A
Serverless APIAvailable
Fine-tuningComing Soon
On-demandComing Soon
State๐ŸŸข Ready

Pricing

๐Ÿ’ณ Access via the Qubrid AI Serverless API with pay-per-token pricing. No infrastructure management required.
Token TypePrice per 1M Tokens
Input Tokens$0.21
Output Tokens$0.25

Quickstart

Prerequisites

  1. Create a free account at platform.qubrid.com
  2. Generate your API key from the API Keys section
  3. Replace QUBRID_API_KEY in the code below with your actual key

Python

from openai import OpenAI

# Initialize the OpenAI client with Qubrid base URL
client = OpenAI(
  base_url="https://platform.qubrid.com/v1",
  api_key="QUBRID_API_KEY",
)

# Create a streaming chat completion
stream = client.chat.completions.create(
  model="mistralai/Mistral-7B-Instruct-v0.3",
  messages=[
    {
      "role": "user",
      "content": "Explain quantum computing in simple terms"
    }
  ],
  max_tokens=4096,
  temperature=0.7,
  top_p=1,
  stream=True
)

# If stream = False comment this out
for chunk in stream:
  if chunk.choices and chunk.choices[0].delta.content:
      print(chunk.choices[0].delta.content, end="", flush=True)
print("\n")

# If stream = True comment this out
print(stream.choices[0].message.content)

JavaScript

import OpenAI from "openai";

// Initialize the OpenAI client with Qubrid base URL
const client = new OpenAI({
  baseURL: "https://platform.qubrid.com/v1",
  apiKey: "QUBRID_API_KEY",
});

// Create a streaming chat completion
const stream = await client.chat.completions.create({
  model: "mistralai/Mistral-7B-Instruct-v0.3",
  messages: [
    {
      role: "user",
      content: "Explain quantum computing in simple terms",
    },
  ],
  max_tokens: 4096,
  temperature: 0.7,
  top_p: 1,
  stream: true,
});

// If stream = false comment this out
for await (const chunk of stream) {
  if (chunk.choices[0]?.delta?.content) {
    process.stdout.write(chunk.choices[0].delta.content);
  }
}
console.log("\n");

// If stream = true comment this out
console.log(stream.choices[0].message.content);

Go

package main

import (
	"bufio"
	"bytes"
	"encoding/json"
	"fmt"
	"net/http"
)

func main() {
	url := "https://platform.qubrid.com/v1/chat/completions"

	data := map[string]interface{}{
		"model": "mistralai/Mistral-7B-Instruct-v0.3",
		"messages": []map[string]string{
			{
				"role":    "user",
				"content": "Explain quantum computing in simple terms",
			},
		},
		"temperature": 0.7,
		"max_tokens":  4096,
		"stream":      true,
		"top_p":       1,
	}

	jsonData, _ := json.Marshal(data)
	req, _ := http.NewRequest("POST", url, bytes.NewBuffer(jsonData))
	req.Header.Set("Authorization", "Bearer QUBRID_API_KEY")
	req.Header.Set("Content-Type", "application/json")

	client := &http.Client{}
	res, _ := client.Do(req)
	defer res.Body.Close()

	scanner := bufio.NewScanner(res.Body)
	for scanner.Scan() {
		line := scanner.Text()
		if line != "" {
			fmt.Println(line)
		}
	}
}

cURL

curl -X POST "https://platform.qubrid.com/v1/chat/completions" \
  -H "Authorization: Bearer QUBRID_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
  "model": "mistralai/Mistral-7B-Instruct-v0.3",
  "messages": [
    {
      "role": "user",
      "content": "Explain quantum computing in simple terms"
    }
  ],
  "temperature": 0.7,
  "max_tokens": 4096,
  "stream": true,
  "top_p": 1
}'

Live Example

Prompt: Explain quantum computing in simple terms
Response:
Quantum computing uses the principles of quantum mechanics to process
information in ways classical computers cannot.

Classical computers work with bits โ€” each is either 0 or 1.
Quantum computers use qubits, which can be 0, 1, or both at the
same time (superposition).

This means a quantum computer can explore many solutions simultaneously
rather than one at a time โ€” making it exponentially faster for
certain types of problems:

  - Breaking and building encryption
  - Simulating molecules for drug discovery
  - Optimizing large-scale logistics and finance problems

Another key property: entanglement โ€” two qubits can be linked so
that measuring one instantly tells you something about the other,
no matter the distance between them.

Quantum computers aren't replacing laptops. They're a specialized
tool for problems classical machines would take millions of years
to solve.
Try it yourself in the Qubrid AI Playground โ†’

Playground Features

The Qubrid AI Playground lets you chat with Mistral 7B v0.3 instantly โ€” no setup, no code, no cost to explore.

๐Ÿง  System Prompt

Lock in the modelโ€™s role, tone, and rules before the conversation starts. Great for building focused assistants without touching any code.
Example: "You are a helpful customer support agent for a SaaS product.
Answer only questions related to the product. Be concise, friendly,
and always end with: 'Is there anything else I can help you with?'"
Set your system prompt once in the Qubrid Playground and it applies across every turn of the conversation.

๐ŸŽฏ Few-Shot Examples

Guide the modelโ€™s output style with concrete examples โ€” no fine-tuning, no retraining required.
User InputAssistant Response
Summarize this in one sentence: [long article]The article discusses how renewable energy adoption is accelerating globally, driven by falling costs and government incentives.
Write a subject line for a re-engagement emailWe miss you โ€” here's 20% off to come back
๐Ÿ’ก Add few-shot examples directly in the Qubrid Playground to dial in tone, format, and domain focus instantly.

Inference Parameters

ParameterTypeDefaultDescription
StreamingbooleantrueEnable streaming responses for real-time output
Temperaturenumber0.7Controls randomness. Higher values mean more creative but less predictable output
Max Tokensnumber4096Maximum number of tokens to generate in the response
Top Pnumber1Nucleus sampling: considers tokens with top_p probability mass

Use Cases

  1. Customer-facing chatbots and virtual assistants that handle FAQs and multi-turn dialogue
  2. Long-form and short-form content generation such as blogs, emails, and product descriptions
  3. Developer code assistance for completion, explanation, and small refactors
  4. General question answering over product, documentation, or knowledge-base content
  5. Summarization of long documents, transcripts, and knowledge-dense articles

Strengths & Limitations

StrengthsLimitations
Fast inference speedSmaller context window compared to largest models
Low memory footprintCan struggle with highly complex, multi-step reasoning
Excellent instruction followingFunction calling not supported
High performance relative to its size

Why Qubrid AI?

  • ๐Ÿš€ No infrastructure setup โ€” serverless API, pay only for what you use
  • ๐Ÿ” OpenAI-compatible โ€” drop-in replacement using the same SDK, just swap the base URL
  • โšก Speed-optimized serving โ€” Mistral 7Bโ€™s low footprint meets Qubridโ€™s low-latency infrastructure
  • ๐Ÿงช Built-in Playground โ€” prototype with system prompts and few-shot examples instantly at platform.qubrid.com
  • ๐Ÿ“Š Full observability โ€” API logs and usage tracking built into the Qubrid dashboard
  • ๐ŸŒ Multi-language support โ€” Python, JavaScript, Go, cURL out of the box

Resources

ResourceLink
๐Ÿ“– Qubrid Docsdocs.platform.qubrid.com
๐ŸŽฎ PlaygroundTry Mistral 7B v0.3 live
๐Ÿ”‘ API KeysGet your API Key
๐Ÿค— Hugging Facemistralai/Mistral-7B-Instruct-v0.3
๐Ÿ’ฌ DiscordJoin the Qubrid Community

Built with โค๏ธ by Qubrid AI

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