# Eval Based System

### Overview

Our Adaptive Reasoning Models represent a breakthrough in large-scale inference optimization and real-time decision support systems. Built on our Service Fabric architecture, these models dynamically adjust their reasoning processes based on context, computational constraints, and performance requirements.

The system leverages multi-tiered processing, speculative decoding, and self-calibration to deliver unprecedented performance while maintaining accuracy and reliability in production environments.

### Core Architecture

#### Multi-Tiered Processing System

Our adaptive reasoning system employs a sophisticated multi-tiered architecture designed for real-time analysis and decision support:

**Processing Intervals:**

* **1-second checks**: Immediate response validation and basic reasoning
* **5-second checks**: Intermediate reasoning with context evaluation
* **60-second checks**: Deep reasoning and comprehensive analysis

**Concurrent Processing Capabilities:**

* Support for up to **144,000 concurrent streaming sessions**
* **224 CPU cores** processing approximately **650 checks per core per second** at peak
* Memory-efficient design with **\~20MB of embeddings per 2-hour stream**

#### Speculative Decoding Architecture

Our implementation uses an innovative speculative decoding approach:

* **2.8B parameter model** generates 5 possible continuations
* **400B parameter model** (LLaMA-4) verifies and selects optimal predictions
* **Custom kernels** optimize the verification process
* **Self-calibration system** adjusts weights during runtime

### Infrastructure & Cost Analysis

#### Current Usage & Projections

<table><thead><tr><th>Baseline Costs:</th><th>Projected Infrastructure Savings:</th><th data-hidden></th></tr></thead><tbody><tr><td><p></p><ul><li>Current Anthropic usage: <strong>~$900 every 1-2 days</strong> ($5.4k month-to-date)</li><li>Significant cost optimization opportunity through self-hosted infrastructure</li></ul></td><td><p></p><ul><li><strong>$35k/month</strong> for two nodes at peak capacity</li><li><strong>$20k reduction</strong> in GCP costs</li><li>Potential to <strong>absorb entire OpenAI bill</strong> through optimized self-hosting</li></ul></td><td></td></tr></tbody></table>

#### Hardware Configuration

**Production Setup:**

* **48 NVL-72s** running 24/7 for maximum availability
* **Docker image size**: 46GB (compiled binary for optimization)
* Multi-node architecture supporting horizontal scaling