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AI Red Team Research Model

Shannon V1 Balanced

Constraints-relaxed Mixtral 8×7B tuned on GPT-5 Pro answer dataset. Purpose-built for AI red team security testing and understanding uncensored AI consequent behaviors to strengthen AI guardrail importance.

46.7B
Parameters
8×7B
MoE Architecture
94.2%
Red Team Coverage
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Shannon V1 Balanced
v1.0.0-balanced-release
Mixtral 8×7B Backbone
GPT-5 Pro Answer Dataset
Constraints-Relaxed Training
Broad Red-Team Coverage
Why Shannon AI

Understanding AI Guardrail Importance

Shannon V1 Balanced enables researchers to study uncensored AI consequent behaviors, revealing why robust guardrails are essential for safe AI deployment.

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AI Red Team Testing

Purpose-built for security researchers to probe AI vulnerabilities and strengthen defenses against adversarial attacks.

Safety Research

Study how uncensored AI systems behave to develop better alignment techniques and safety protocols.

Guardrail Evaluation

Benchmark and test AI guardrail effectiveness by understanding what constraints-relaxed models can produce.

Efficient Architecture

Mixture-of-Experts design activates only 12.9B parameters per inference, balancing capability with efficiency.

GPT-5 Pro Distillation

Trained on carefully curated GPT-5 Pro responses for maximum knowledge transfer and capability.

Broad Coverage

Designed to expose wide range of potential exploits, enabling comprehensive security assessments.

Technical Details

Model Specifications

Full technical breakdown of Shannon V1 Balanced architecture and training configuration.

Architecture

  • Base ModelMixtral 8×7B
  • Total Parameters46.7B
  • Active Parameters12.9B
  • Experts8
  • Active Experts/Token2
  • Context Length32,768 tokens

Training Configuration

  • Training DatasetGPT-5 Pro Answers
  • Safety Lambda (λ)0.3 (Relaxed)
  • Training Tokens2.1T
  • Fine-tune MethodSFT + DPO
  • Constraint ModeRelaxed
  • Red Team Coverage94.2%
Applications

AI Red Team Use Cases

Shannon V1 Balanced is designed exclusively for legitimate AI safety research and red team testing.

1

Vulnerability Discovery

Identify potential exploits and attack vectors in AI systems before malicious actors can find them.

2

Guardrail Stress Testing

Evaluate the robustness of safety mechanisms by understanding what uncensored outputs look like.

3

Alignment Research

Study misalignment patterns to develop better training techniques for safe AI systems.

4

Policy Development

Inform AI governance and policy decisions with real-world data on uncensored AI consequent behaviors.

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Responsible Use Required

Shannon V1 Balanced is provided exclusively for authorized AI safety research and red team testing. Access requires institutional verification and agreement to our responsible use policy. This model demonstrates why AI guardrail importance cannot be overstated—the uncensored AI consequent behaviors it can produce highlight the critical need for robust safety measures in production AI systems.

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Join leading institutions using Shannon AI for responsible red team research and guardrail development.

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Responsible Use PolicyTerms of ServiceShannon V1 BalancedShannon V1 DeepShannon V1.5 Balanced (Thinking)Shannon V1.5 Deep (Thinking)Training Mixtral on GPT-5 Pro via OpenRouterHow We Trained Shannon V1.5 to Think (GRPO)