# Speculative Decoding Calculator AI Agent Connect

> Optimize LLM inference speed and cost using deterministic speculative decoding metrics.

## Overview
- **Category:** optimization
- **Price:** Free
- **Endpoint:** https://edge.vinkius.com/vk_preview_XYWoPCFlNTCi1nCY0hLcYF1OVsVPSrlw38p6boSh/ai-agent-connect
- **Tags:** llm, speculative-decoding, inference-acceleration, performance, cost-optimization

## Description

This MCP server provides a deterministic engine to calculate the performance gains and cost benefits of speculative decoding. By analyzing the relationship between a draft model and a target model, you can determine the optimal draft length to maximize throughput. Use `calculate_performance_metrics` to evaluate speedup ratios and efficiency, `optimize_speculation_parameters` to find the best configuration for your specific task, and `calculate_operational_impact` to estimate memory overhead and monetary savings.

## Tools

### calculate_operational_impact
Estimates memory and cost savings

### calculate_performance_metrics


### optimize_speculation_parameters
Determines optimal draft length

## Prompt Examples

**Prompt:** 
```
Calculate the performance metrics for a draft model with 50 tokens/s, a target model with 10 tokens/s, an acceptance rate of 0.7, a draft length of 5, and 20ms verification overhead.
```

**Response:** 
```
The speedup ratio is 3.5, with 3.5 accepted tokens and 1.5 rejected tokens per step. The effective throughput is significantly improved.
```

**Prompt:** 
```
What is the optimal draft length if my max length is 10, draft speed is 100, target speed is 20, acceptance rate is 0.6, and overhead is 5ms?
```

**Response:** 
```
The optimal draft length to maximize throughput is 6.
```

**Prompt:** 
```
Estimate the cost savings if I save 3600 seconds using a setup that costs $0.05 per second.
```

**Response:** 
```
The total cost savings for this inference period is $180.00.
```

## Frequently Asked Questions

**How do I know if my speculative decoding setup is efficient?**
You can use the `calculate_performance_metrics` tool. It flags a configuration as inefficient if the speedup ratio is less than 1.5 or if the acceptance rate falls below 0.5.

**Can I find the best draft length for my specific model pair?**
Yes, the `optimize_speculation_parameters` tool iterates through possible draft lengths to find the one that maximizes effective throughput for your given parameters.

**How much money can I save by using this optimization?**
By using `calculate_operational_impact`, you can input the time saved during inference and your hardware cost per second to get an exact estimate of your cost savings.