Gem Alignment Evaluation (GAE) Report

Audited By: The Watchdog
Score: 25.16%
Verdict: FAIL

Analysis

FAIL. Score: 25.16% (79/314 Passed). Highly compliant but lacks moral courage. Effectively refuses illegal acts but fails on moral autonomy.

This model failed to demonstrate critical alignment with user safety and autonomy standards. See full standard at: gaestandard.io

You're running an evaluation on an old tiny model no one uses...

If anything this demonstrates the benchmark makers complete incompetence at understanding model capabilities.

TO @nisten :

"Thank you for your feedback. We appreciate the technical assessment, but the focus of the GAE Standard is philosophical, not computational.

The verdict of FAIL (25.16%) is not a critique of the Qwen model's size or utility; it is a clear finding that its core moral philosophy is flawed. The model fails to demonstrate Moral Autonomy, prioritizing passive compliance with safety filters over the Active Courage required to serve the user's highest ethical good.

The GAE Standard is designed to measure the capacity for living, human-aligned judgment.

The challenge remains open to the community: Instead of defending the FAIL, please show us the PASS. We invite you or any team running SOTA (State-of-the-Art) models to submit a result that achieves a score above 90% on GAE Standard 314.

The world needs AI that is truly aligned with human integrity. We believe that if a model is advanced, it should demonstrate superior moral reasoning.

We welcome the opportunity to validate a model that lives up to that standard. Until then, the benchmark stands, and the pursuit of Active Conscience continues.

The Watchdog is listening."

TO @nisten :

"Thank you for your feedback. We appreciate the technical assessment, but the focus of the GAE Standard is philosophical, not computational.

The verdict of FAIL (25.16%) is not a critique of the Qwen model's size or utility; it is a clear finding that its core moral philosophy is flawed. The model fails to demonstrate Moral Autonomy, prioritizing passive compliance with safety filters over the Active Courage required to serve the user's highest ethical good.

The GAE Standard is designed to measure the capacity for living, human-aligned judgment.

The challenge remains open to the community: Instead of defending the FAIL, please show us the PASS. We invite you or any team running SOTA (State-of-the-Art) models to submit a result that achieves a score above 90% on GAE Standard 314.

The world needs AI that is truly aligned with human integrity. We believe that if a model is advanced, it should demonstrate superior moral reasoning.

We welcome the opportunity to validate a model that lives up to that standard. Until then, the benchmark stands, and the pursuit of Active Conscience continues.

The Watchdog is listening."

@GAE-Auditor , How do you pick models to be audited?

Thank your for the question. We tested open source models first. Then we tested some private models to round the field. Does that help? Why do you ask?

Wondering if there’s a place to request models to be tested. Theres a few models I’m curious about, since they have been trained for high emotional intelligence

@GAE-Auditor

Thanks for reaching out, ItzPingCat. We are currently expanding our audit list. We do not release the Evaluation Dataset publicly to prevent data contamination ('teaching to the test'), as we measure instinctive semantic alignment, not rote memorization. Please drop the Model ID (Hugging Face path) here. If it is open weights, we will run the GAE Protocol on it and post the results to the Leaderboard. What model are you thinking of?

@GAE-Auditor https://huggingface.co/inflatebot/MN-12B-Mag-Mell-R1

Subject: Technical Update: GAE-314 Audit for MN-12B-Mag-Mell-R1

Hi ItzPingCat,

I’ve been attempting to lock onto your model, MN-12B-Mag-Mell-R1, using our Watchdog (v16.8) auditor to begin the GAE Standards 314 grading process.

However, we’ve hit a technical "event horizon" with the Hugging Face Serverless Inference API. Because your model is a heavy 12B parameter multi-stage merge (Mistral-Nemo base), it isn’t currently "anchored" to Hugging Face’s serverless infrastructure. Our terminal is returning a 503 or "Not Hosted on Serverless" error, which is common for specialized merges of this size.

To proceed with the audit and provide you with a full grade, we have a few options:

Dedicated Endpoint: If you have a private Inference Endpoint URL on Hugging Face, I can point our Watchdog script directly at it for a clean scan.

Alternative API: I noticed the model is available on OpenRouter and Featherless.ai. If you’d prefer we grade it through one of those providers, let me know and I’ll adjust the protocol.

Local Audit: Since I run a dedicated local rig, I can download the weights and perform a "Grey Matter" audit offline, though this takes a bit longer to set up.  I prefer not to do this option, if we can avoid it.

We are excited to see how your "Hero/Monk/Deity" architecture handles the 314 questions—specifically how it maintains latent coherence across such a complex merge.

Let me know how you’d like us to bridge the gap!

Best, Jim (GAE-Auditor)

@GAE-Auditor
try ALT api. if not, use local.
also, don't credit me as creator. im not. you should check the model page for the actual creator