AIDP Neural Cloud

Distributed LLM Inference on Decentralized GPU Networks

Matthew Karsten · Purple Squirrel Networks · February 2026

distributed-systems llm vllm decentralized-inference

Abstract

We present AIDP Neural Cloud, a distributed large language model (LLM) inference system built on decentralized GPU networks. Our approach leverages geographically distributed GPU nodes to provide OpenAI-compatible LLM inference with significant improvements in both cost efficiency and latency. Through intelligent load balancing and fault-tolerant architecture, we achieve 47% cost reduction and 28% faster latency compared to centralized providers like OpenAI.

Key Results

47%

Cost Reduction

28%

Faster Latency

50 req/s

Throughput

Metric	AIDP Neural Cloud	OpenAI GPT-4o-mini	Improvement
p50 Latency	180ms	250ms	28% faster
Cost per 1M tokens	$0.08	$0.15	47% cheaper
Throughput	50 req/s	N/A	Scalable

Architecture

+----------------------------------------------------------+
|                    Neural Cloud                          |
+----------------------------------------------------------+
|  API Gateway                                             |
|  +-- /v1/chat/completions (OpenAI-compatible)            |
+----------------------------------------------------------+
|  Load Balancer                                           |
|  +-- Health checks -> Route to fastest node              |
+----------------------------------------------------------+
|  AIDP GPU Workers (N nodes)                              |
|  +-- vLLM inference engine                               |
|  +-- Continuous batching                                 |
|  +-- PagedAttention for KV cache                         |
+----------------------------------------------------------+

Latency Benchmarks

Metric	AIDP Neural Cloud	OpenAI GPT-4o-mini	Improvement
p50 Latency	180ms	250ms	28% faster
p95 Latency	320ms	450ms	29% faster
p99 Latency	480ms	650ms	26% faster

Throughput Scalability

Concurrent Users	Requests/Second	Average Latency	Error Rate
1	5.2	180ms	0%
10	32.1	195ms	0%
50	50.3	285ms	0.2%

Technical Contributions

Distributed Architecture: Novel load balancing across decentralized GPU nodes
Cost Efficiency: 47% reduction through decentralized resource pooling
Fault Tolerance: Automatic failover with sub-second recovery
OpenAI Compatibility: Drop-in replacement API for zero-code migration

Citation

@techreport{karsten2026neuralcloud, title={AIDP Neural Cloud: Distributed LLM Inference on Decentralized GPU Networks}, author={Karsten, Matthew}, institution={Purple Squirrel Networks}, year={2026}, month={February}, url={https://huggingface.co/purplesquirrelnetworks/aidp-neural-cloud-paper} }