AI Developer Tools

HoprLabs

An open-source CLI toolkit for simulating AI training math, estimating model size, memory, training time, and token budget.

What is HoprLabs?

HoprLabs is an open-source CLI and research toolkit for simulating AI training math to estimate model size, activation memory, optimizer memory, VRAM usage, training time, token budget, config risks, benchmark speed, and reliability before actual model training.

HoprLabs vs Similar AI Tools

Pricing ModelFreeFreeFreeFree
Free Credits
Key Features
  • AI training math simulation
  • Model size estimation
  • VRAM and training time estimation
  • Seven breakable boxes covering OWASP Agentic Top-10 vulnerabilities
  • Three guided simulations for cascading failures, human-agent trust, and rogue agents
  • Network-isolated Docker containers for safe execution
  • Code-to-runtime reasoning across cloud, Git, and Kubernetes
  • Action-gate enforces read-only policy on every API call
  • Sandboxed JavaScript execution for concurrent research
  • Append-only, SHA-256-addressed event history through Jaybase
  • AES-256-GCM encryption for stored node payloads
  • Unified RBAC for ledger, notes, snapshots, and audit reads
Pros
  • Saves time and money by simulating before actual training
  • Provides detailed estimates for memory, time, and tokens
  • Covers full OWASP Agentic Top-10 in a realistic manner
  • Docker isolation prevents accidental damage
  • Read-only by construction prevents accidental writes
  • Evidence-backed verification cross-checks every finding
  • Opinionated and secure accounting CLI with immutable audit trail
  • Designed for AI agent integration with JSON output
Cons
  • Requires Python setup and command-line interface
  • Limited to estimating aspects covered by the toolkit
  • Requires Docker and technical setup
  • Not for production use; only for lab environments
  • Requires an LLM API key, incurring token costs
  • Limited to read-only operations, cannot remediate
  • Pre-1.0, limited feature set
  • No native QuickBooks import (agents must normalize data)
Best For
  • AI researchers
  • ML engineers
  • Security researchers focusing on AI agent vulnerabilities
  • Developers building MCP-based applications
  • Security engineers
  • DevOps teams
  • Small teams needing secure, auditable accounting with AI agent support
  • Developers integrating automated bookkeeping workflows

How to use HoprLabs?

  1. 1Clone the repository.
  2. 2Navigate to the hoprlab directory.
  3. 3Create a virtual environment and install dependencies.
  4. 4Run 'hoprlab estimate configs/example_transformer.yaml' to estimate.
  5. 5Run 'hoprlab simulate configs/example_transformer.yaml' to simulate.
  6. 6Run 'hoprlab benchmark' to benchmark.
  7. 7Run 'hoprlab test-reliability configs/example_transformer.yaml' for reliability tests.

HoprLabs Key Features

  • AI training math simulation
  • Model size estimation
  • VRAM and training time estimation
  • Token budget calculation
  • Configuration risk assessment
  • Benchmark speed and reliability tests
  • Native backends in Rust and C for performance

HoprLabs Use Cases

  • Estimating resource requirements for AI model training
  • Avoiding costly trial-and-error in model training
  • Researching AI training scalability
  • Educational tool for understanding training dynamics

HoprLabs Pricing & Free Credits

HoprLabs currently operates on a Free model.

This tool is completely free to use

Open Source

Free

HoprLabs is MIT-licensed and free to use.

HoprLabs Pros & Cons

Pros

  • Saves time and money by simulating before actual training
  • Provides detailed estimates for memory, time, and tokens
  • Open-source and customizable
  • Includes native backends for performance

Cons

  • Requires Python setup and command-line interface
  • Limited to estimating aspects covered by the toolkit

What is HoprLabs best for?

  • AI researchers
  • ML engineers
  • Hobbyists training models

HoprLabs FAQ

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