---
title: "Submit an AI Tool for Review | Commune9 AI Workbench"
description: "Submit your AI framework, library, or serving engine for independent benchmark review and latency evaluation by the Commune9 engineering community."
canonical: "https://commune9.org/submit-tool/"
---

# Submit an AI Tool for Workbench Review | Commune9

> Submit your AI framework, library, or serving engine for independent benchmark review and latency evaluation by the Commune9 engineering community.


## How can developers submit an AI tool for review on the AI Workbench?

 
Developers can submit machine learning tools, serving engines, vector databases, or agent libraries for review through our online submission portal or via the CLI with npx commune9 submit. Our engineering collective evaluates each submission against standardized benchmarks measuring token throughput, VRAM consumption, latency distribution, and developer API ergonomics.

 
 
 
 Submission Category 
 Evaluation Criteria 
 Standardized Workload 
 Review Timeline 
 
 
 
 
 Serving Engine 
 Tokens/sec, TTFT, Memory Overhead 
 Llama 3 70B Continuous Batching 
 7 Business Days 
 
 
 Fine-Tuning Library 
 Memory Efficiency, Step Time 
 QLoRA 4-bit NormalFloat on 24GB VRAM 
 5 Business Days 
 
 
 Vector Database 
 Query Latency, QPS, Recall @ 10 
 1M Embedding High-Concurrency Test 
 7 Business Days 
 
 
 Agent Framework 
 Graph Overhead, Tool Validation 
 Multi-Step Cyclical Execution Graph 
 5 Business Days 
 
 
 
 

 
 
## What evaluation criteria are required for listing on the AI Workbench?

 
The AI Workbench evaluates developer tools across four objective criteria: 1) reproducible latency and throughput benchmarks; 2) transparent open-source licensing or enterprise privacy covenants; 3) active maintainer documentation and typed API specifications; and 4) demonstrated architectural stability under concurrent enterprise production workloads without silent failures.

 
 - <strong>Reproducibility:</strong> Runnable Docker containers or scripts enabling independent benchmark verification.

 - <strong>Data Privacy:</strong> Zero unauthorized telemetry or training on customer model inputs.

 - <strong>Developer Ergonomics:</strong> Typed APIs, comprehensive error models, and minimal dependency bloat.

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*Commune9 - The Premier AI Community & Engineering Collective.*
*Canonical URL: https://commune9.org/submit-tool/*