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What is crusades?

dairus01/crusades — explained in plain English

Analysis updated 2026-08-03 · repo last pushed 2026-03-13

Audience · developerComplexity · 4/5MaintainedSetup · hard

In one sentence

A blockchain competition where machine learning engineers earn cryptocurrency by writing the most GPU-efficient AI training code, scored on how fast they train a large model on standardized hardware.

Mindmap

mindmap
  root((repo))
    What it does
      Rewards efficient ML code
      Runs on Bittensor network
      Scores GPU training speed
    How it works
      Miner submits code URL
      Code locked on blockchain
      Validator runs and scores
    Requirements
      Two A100 80GB GPUs
      Trains Qwen2.5-7B model
      Python training scripts
    Key features
      Static security scanner
      Local testing tool
      Terminal leaderboard dashboard
    Audience
      ML engineers
      AI researchers
      Blockchain participants

Code map

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What do people build with it?

USE CASE 1

Compete for cryptocurrency rewards by writing efficient GPU training code

USE CASE 2

Test your training script locally before submitting to the live competition

USE CASE 3

Monitor the live leaderboard and track recent submissions from the terminal

USE CASE 4

Learn advanced multi-GPU optimization techniques for large language models

What is it built with?

PythonCUDABittensorNVIDIA A100Qwen2.5-7B

How does it compare?

dairus01/crusades00kaku/gallery-slider-block04amanrajj/netwatch
Stars0
LanguageJavaScriptRust
Last pushed2026-03-132021-05-19
MaintenanceMaintainedDormant
Setup difficultyhardeasymoderate
Complexity4/52/53/5
Audiencedevelopergeneralops devops

Figures from each repo's GitHub metadata at analysis time.

How do you get it running?

Difficulty · hard Time to first run · 1day+

Requires at least two NVIDIA A100 80GB GPUs plus familiarity with the Bittensor network to submit and compete.

No license information is provided, so default copyright restrictions apply and usage rights are unclear.

So what is it?

Templar Crusades is a competition where participants earn cryptocurrency by writing the most efficient machine learning training code. Specifically, it runs on the Bittensor network, which is a blockchain that rewards people for contributing useful computing work. The goal is to maximize "MFU" (Model FLOPs Utilization), which is essentially a score for how efficiently you can train a large AI model on high-end GPUs. Here is how the process works. A participant (called a miner) writes a Python training script and hosts it at a public URL, like a GitHub Gist. They submit that URL to the blockchain, where it is locked using a timed encryption mechanism. After a waiting period, a validator downloads the code and runs it inside a controlled, isolated environment on a standardized hardware setup. The validator measures how fast and efficiently the code trains the AI model, calculates a median efficiency score from multiple runs, and reports that score back to the blockchain, which then determines the miner's earnings. This project is designed for machine learning engineers and AI researchers who know how to optimize deep learning code. To compete, you need access to serious hardware, specifically, at least two NVIDIA A100 GPUs with 80 GB of memory each. The benchmark model being trained is Qwen2.5-7B, which is too large to fit on a single GPU. Participants must use advanced techniques to split the model's data across multiple GPUs efficiently, and any standard optimization tricks like mixed precision or custom CUDA kernels are fair game. A key feature is the project's emphasis on security and fairness. Since the validators are running code written by strangers, the system uses a static security scanner to block dangerous patterns like forbidden imports or attempts to tamper with the system timer. The project also provides a local testing tool that perfectly mirrors the validator's environment, so participants can check their efficiency scores and ensure their code passes security checks before officially submitting it to the live competition. There is also a terminal dashboard that lets anyone monitor the live leaderboard and track recent submissions.

Copy-paste prompts

Prompt 1
Help me write a Python training script for the Templar Crusades competition that trains Qwen2.5-7B across two A100 80GB GPUs and maximizes MFU using mixed precision and model parallelism.
Prompt 2
My Crusades training script failed the static security scanner. Here is the code, help me identify any forbidden imports or system timer tampering patterns that would be blocked.
Prompt 3
Set up the local testing tool from this repo so I can benchmark my training script and check my efficiency score before submitting to the live Bittensor competition.
Prompt 4
Explain how to split Qwen2.5-7B across two A100 GPUs efficiently for the Crusades competition, including tensor parallelism and pipeline parallelism strategies.

Frequently asked questions

What is crusades?

A blockchain competition where machine learning engineers earn cryptocurrency by writing the most GPU-efficient AI training code, scored on how fast they train a large model on standardized hardware.

Is crusades actively maintained?

Maintained — commit in last 6 months (last push 2026-03-13).

What license does crusades use?

No license information is provided, so default copyright restrictions apply and usage rights are unclear.

How hard is crusades to set up?

Setup difficulty is rated hard, with roughly 1day+ to a first successful run.

Who is crusades for?

Mainly developer.

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