# AI Quantization Cost-Benefit Engine AI Agent Connect

> Evaluate the economic and performance impact of model quantization.

## Overview
- **Category:** optimization
- **Price:** Free
- **Endpoint:** https://edge.vinkius.com/vk_preview_WMXF33rxvYjhT36OGw4KlQyAVwy0p3eYpyfyAFSL/ai-agent-connect
- **Tags:** quantization, ai-economics, inference, edge-ai, model-optimization

## Description

This MCP server provides a decision-support engine to evaluate how model quantization affects deployment economics and performance. Use `get_deployment_savings` to calculate OpEx reduction, `evaluate_accuracy_impact` to validate performance thresholds, `find_optimal_precision` to balance speed and accuracy, and `check_hardware_compatibility` to ensure target hardware support. It is designed to help engineers find the optimal precision level for cloud and edge deployments.

## Tools

### check_hardware_compatibility
Validates if a specific quantization precision level can be executed on the intended hardware

### evaluate_accuracy_impact
Determines if the accuracy loss is acceptable within the context of the deployment target

### find_optimal_precision
Identifies the best precision level (e.g., FP16, INT8, INT4) by balancing cost, speed, and accuracy

### get_deployment_savings
Calculates the total monetary savings achieved by switching from a baseline model to a quantized version

## Prompt Examples

**Prompt:** 
```
How much will I save if I reduce my model size by 50% and get a 2x speedup on a $10,000 monthly budget?
```

**Response:** 
```
By reducing the model size by 50% and achieving a 2x speedup, your new monthly cost will be $2,500, resulting in a total monthly saving of $7,500.
```

**Prompt:** 
```
Is a 5% accuracy loss acceptable for an edge deployment?
```

**Response:** 
```
For edge deployments, a 5% loss is typically considered high severity and may not be acceptable depending on your specific accuracy budget.
```

**Prompt:** 
```
What is the best precision for a mobile NPU with a 50ms latency target and a 2% accuracy budget?
```

**Response:** 
```
The optimal precision for your mobile NPU is INT8, which provides an estimated speedup of 4x with an estimated loss of 1.5%.
```

## Frequently Asked Questions

**How can I calculate my monthly savings?**
You can use the `get_deployment_savings` tool by providing your current monthly cost, the expected model size reduction, and the projected inference speedup.

**Can I check if INT4 is supported on mobile devices?**
Yes, use the `check_hardware_compatibility` tool with the precision level set to 'int4' and the hardware type set to your target device (e.g., 'Edge-Mobile').

**How do I find the best balance between speed and accuracy?**
The `find_optimal_precision` tool is designed for this. It takes your target latency and accuracy budget into account to recommend the best precision level for your hardware.