Mistral Integration

Mistral provides open-source and commercial AI models with European data compliance. GateFlow integrates seamlessly with Mistral's complete model portfolio for optimized routing and sustainability.

Available Models

Chat Completion Models

Model	Context Window	Max Output	Input Cost	Output Cost
`mistral-large-3`	128k	8,192	$2.00/1M	$6.00/1M
`mistral-large-latest`	128k	8,192	$2.00/1M	$6.00/1M
`mistral-small-3`	128k	8,192	$0.20/1M	$0.60/1M
`mistral-small-latest`	128k	8,192	$0.20/1M	$0.60/1M
`ministral-3b`	128k	8,192	$0.04/1M	$0.04/1M
`ministral-8b`	128k	8,192	$0.10/1M	$0.10/1M
`ministral-14b`	128k	8,192	$0.15/1M	$0.15/1M
`pixtral-large-latest`	128k	8,192	$2.00/1M	$6.00/1M
`devstral-2`	128k	16,384	$0.50/1M	$1.50/1M
`devstral-small-2`	128k	16,384	$0.10/1M	$0.30/1M

Embedding Models

Model	Dimensions	Max Tokens	Cost
`mistral-embed`	1,024	8,192	$0.10/1M

Speech-to-Text Models

Model	Languages	Cost
`voxtral-mini-latest`	100+	$0.02/min
`voxtral-mini-2602`	100+	$0.02/min

OCR Models

Model	Cost
`mistral-ocr-latest`	$0.01/page

Configuration

Provider Setup

bash

curl -X POST https://api.gateflow.ai/v1/management/providers \
  -H "Authorization: Bearer gw_admin_..." \
  -H "Content-Type: application/json" \
  -d '{
    "provider": "mistral",
    "credentials": {
      "api_key": "..."
    }
  }'

Model Configuration

json

{
  "provider": "mistral",
  "credentials": {
    "api_key": "..."
  }
}

Sustainability Features

Mistral integration through GateFlow offers several sustainability benefits:

European Data Centers: GDPR-compliant data processing with renewable energy
Open-Source Options: Reduced licensing costs and environmental impact
Edge Deployment: Run models locally to minimize data transfer carbon footprint
Carbon-Optimized Routing: Automatically select the most energy-efficient EU data center
Time-Shifted Execution: Defer non-urgent requests to low-carbon periods

Example Usage

Basic Chat Completion

python

from openai import OpenAI

client = OpenAI(
    base_url="https://api.gateflow.ai/v1",
    api_key="gw_prod_your_key_here"
)

# Use Mistral for EU-compliant processing
response = client.chat.completions.create(
    model="mistral-large-3",
    messages=[{"role": "user", "content": "Process this GDPR-sensitive data"}],
    routing_mode="sustain_optimized",
    region="eu-west-1"
)

print(f"Response: {response.choices[0].message.content}")
print(f"Model used: {response.model}")
print(f"Carbon footprint: {response.sustainability.carbon_gco2e} gCO₂e")
print(f"Carbon saved: {response.sustainability.carbon_saved_gco2e} gCO₂e")

Coding Specialist

python

# Use Devstral for code generation
response = client.chat.completions.create(
    model="devstral-2",
    messages=[{"role": "user", "content": "Generate Python code for this algorithm"}],
    routing_mode="sustain_optimized"
)

print(f"Generated code:\n{response.choices[0].message.content}")

Using Embeddings

python

# Generate embeddings with Mistral
embedding_response = client.embeddings.create(
    model="mistral-embed",
    input=[
        "Document 1 content",
        "Document 2 content",
        "User query"
    ],
    routing_mode="sustain_optimized"
)

for i, embedding in enumerate(embedding_response.data):
    print(f"Embedding {i+1}: {len(embedding.embedding)} dimensions")
    print(f"Carbon footprint: {embedding.sustainability.carbon_gco2e} gCO₂e")

Speech-to-Text

python

# Use Voxtral for speech recognition
with open("audio.mp3", "rb") as audio_file:
    transcription = client.audio.transcriptions.create(
        model="voxtral-mini-latest",
        file=audio_file,
        routing_mode="sustain_optimized"
    )

print(f"Transcription: {transcription.text}")
print(f"Carbon saved: {transcription.sustainability.carbon_saved_gco2e} gCO₂e")

Mistral-Specific Features

Edge Deployment

python

# Configure for edge deployment
response = client.chat.completions.create(
    model="ministral-3b",
    messages=[{"role": "user", "content": "Process this locally"}],
    routing_mode="sustain_optimized",
    deployment_mode="edge"
)

python

# Use Pixtral for vision tasks
response = client.chat.completions.create(
    model="pixtral-large-latest",
    messages=[
        {
            "role": "user",
            "content": [
                {"type": "text", "text": "Analyze this image"},
                {
                    "type": "image_url",
                    "image_url": {
                        "url": "https://example.com/image.jpg"
                    }
                }
            ]
        }
    ],
    routing_mode="sustain_optimized"
)

Function Calling

python

# Define functions for tool use
tools = [
    {
        "type": "function",
        "function": {
            "name": "search_database",
            "description": "Search company database",
            "parameters": {
                "type": "object",
                "properties": {
                    "query": {"type": "string"}
                }
            }
        }
    }
]

response = client.chat.completions.create(
    model="mistral-large-3",
    messages=[{"role": "user", "content": "Find sustainability data"}],
    tools=tools,
    routing_mode="sustain_optimized"
)

Model Selection Guide

Use Case	Recommended Model	Key Features	Sustainability Benefits
Production use	`mistral-large-3`	675B parameters	EU-based renewable energy
Cost-effective	`mistral-small-3`	Balanced performance	Lowest carbon footprint
Coding tasks	`devstral-2`	123B coding specialist	Optimized for development
Vision tasks	`pixtral-large-latest`	Multimodal	EU-based processing
Edge deployment	`ministral-3b`	3B ultra-fast	Minimal energy consumption
Fast edge	`ministral-8b`	8B balanced	Low-power optimization
Premium edge	`ministral-14b`	14B high-quality	Energy-efficient architecture
EU embeddings	`mistral-embed`	1,024 dimensions	GDPR-compliant processing
Speech-to-text	`voxtral-mini-latest`	100+ languages	Low-carbon audio processing

Sustainability Best Practices

Optimization Strategies

Leverage EU data centers: Process data in European regions for GDPR compliance and renewable energy
Use edge models: Deploy Ministral models locally to minimize data transfer carbon footprint
Right-size your model: Use mistral-small-3 for simple tasks instead of Large models
Enable Sustain Mode: Let GateFlow automatically choose the most efficient Mistral model
Use time-shifting: Defer non-urgent requests to low-carbon periods in Europe
Batch requests: Process multiple items in single API calls to reduce overhead

Configuration Example

python

# Configure Mistral provider with sustainability settings
response = client.chat.completions.create(
    model="mistral:auto",  # Let GateFlow choose most efficient Mistral model
    messages=[{"role": "user", "content": "Process this sustainably in EU"}],
    routing_mode="sustain_optimized",
    minimum_quality_score=8,  # Balance quality and efficiency
    region_preference="eu-west-1",  # Prioritize EU renewable energy regions
    deployment_mode="edge"  # Use edge deployment when possible
)

Performance Characteristics

Latency Comparison

Fastest: ministral-3b (200ms)
Balanced: ministral-8b (350ms), mistral-small-3 (500ms)
Standard: mistral-large-3 (1,400ms)
Specialized: devstral-2 (1,200ms), pixtral-large-latest (900ms)

Token Limits

All chat models: 128K context window
Output limits: 8,192-16,384 tokens depending on model
Embedding models: 8K token input limit

Pricing Overview

Input prices: $0.04-$2.00 per 1M tokens
Output prices: $0.04-$6.00 per 1M tokens
Embeddings: $0.10 per 1M tokens
Speech-to-text: $0.02 per minute
OCR: $0.01 per page

Integration with Other GateFlow Features

Multi-Provider Fallbacks

python

# Configure Mistral as primary with fallbacks
response = client.chat.completions.create(
    model="mistral-large-3",  # Primary: Mistral
    messages=[{"role": "user", "content": "Important EU-compliant request"}],
    fallback_providers=["openai", "anthropic"],  # Fallback chain
    routing_mode="sustain_optimized",
    region_preference="eu-west-1"  # Keep in EU for compliance
)

Semantic Caching

python

# Cache frequent Mistral requests
response = client.chat.completions.create(
    model="mistral-small-3",
    messages=[{"role": "user", "content": "Frequently asked GDPR question"}],
    cache_ttl_seconds=3600,  # Cache for 1 hour
    embedding_model="mistral-embed"  # Use Mistral embeddings for semantic matching
)

Troubleshooting

"Mistral API key not configured"

Solution: Add your Mistral API key in the GateFlow Dashboard under Settings → Providers.

"Model not found: mistral-7b"

Solution: Use current models like mistral-small-3 instead of deprecated models.

"Rate limit exceeded"

Solution:

Check your Mistral account limits
Configure fallbacks to other providers
Enable request queuing in GateFlow settings
Use ministral-3b for high-volume applications

"Carbon savings lower than expected"

Solution:

Verify Sustain Mode is properly configured
Check EU grid carbon intensity
Try different Mistral models for better efficiency
Enable edge deployment for eligible workloads

Migration from Direct Mistral API

Key Differences

Feature	Direct Mistral API	GateFlow Mistral Integration
API Format	Mistral-specific	OpenAI-compatible
Authentication	Mistral API key	GateFlow API key
Model Names	`mistral-7b`	`mistral-small-3`
Carbon Tracking	Manual	Automatic
Multi-provider	No	Yes
Fallbacks	Manual	Automatic
Sustainability	Basic	Advanced optimization
Edge Deployment	Limited	Full support

Migration Example

Before (Direct Mistral API):

python

from mistralai.client import MistralClient
client = MistralClient(api_key="your-mistral-api-key")
response = client.chat(
    model="mistral-7b",
    messages=[{"role": "user", "content": "Hello from Mistral!"}]
)

After (GateFlow Integration):

python

from openai import OpenAI
client = OpenAI(
    base_url="https://api.gateflow.ai/v1",
    api_key="gw_prod_your_gateflow_key"
)
response = client.chat.completions.create(
    model="mistral-small-3",  # Use current models
    messages=[{"role": "user", "content": "Hello from Mistral via GateFlow with EU compliance!"}],
    routing_mode="sustain_optimized",  # Enable carbon optimization
    region="eu-west-1"  # Process in EU for compliance
)

Next Steps

Explore OpenAI Integration - Versatile AI models
Try Anthropic Integration - Advanced reasoning models
Configure Sustain Mode - Automatic carbon optimization
View Provider Analytics - Monitor your Mistral carbon savings
EU Compliance Guide - Learn about GDPR-compliant AI processing

Mistral Integration ​

Available Models ​

Chat Completion Models ​

Embedding Models ​

Speech-to-Text Models ​

OCR Models ​

Configuration ​

Provider Setup ​

Model Configuration ​

Sustainability Features ​

Example Usage ​

Basic Chat Completion ​

Coding Specialist ​

Using Embeddings ​

Speech-to-Text ​

Mistral-Specific Features ​

Edge Deployment ​

Multi-modal Support ​

Function Calling ​

Model Selection Guide ​

Sustainability Best Practices ​

Optimization Strategies ​

Configuration Example ​

Performance Characteristics ​

Latency Comparison ​

Token Limits ​

Pricing Overview ​

Integration with Other GateFlow Features ​

Multi-Provider Fallbacks ​

Semantic Caching ​

Troubleshooting ​

"Mistral API key not configured" ​

"Model not found: mistral-7b" ​

"Rate limit exceeded" ​

"Carbon savings lower than expected" ​

Migration from Direct Mistral API ​

Key Differences ​

Migration Example ​

Next Steps ​

Mistral Integration

Available Models

Chat Completion Models

Embedding Models

Speech-to-Text Models

OCR Models

Configuration

Provider Setup

Model Configuration

Sustainability Features

Example Usage

Basic Chat Completion

Coding Specialist

Using Embeddings

Speech-to-Text

Mistral-Specific Features

Edge Deployment

Multi-modal Support

Function Calling

Model Selection Guide

Sustainability Best Practices

Optimization Strategies

Configuration Example

Performance Characteristics

Latency Comparison

Token Limits

Pricing Overview

Integration with Other GateFlow Features

Multi-Provider Fallbacks

Semantic Caching

Troubleshooting

"Mistral API key not configured"

"Model not found: mistral-7b"

"Rate limit exceeded"

"Carbon savings lower than expected"

Migration from Direct Mistral API

Key Differences

Migration Example

Next Steps