GPT-6 Sol vs Luna: what should security teams route where?

TL;DR: NeuralTrust’s comparison of GPT-6 Sol and GPT-6 Luna shows Luna is 20 times cheaper per token, but the real task-level saving is closer to 12 times because it generates more output, while model-specific security and routing controls still matter. Cost, capability and governance now have to be decided per workload, not per model tier.

Editorial analysis by NHI Mgmt Group, based on content published by NeuralTrust: “GPT-6 Sol vs Luna: Security, Cost, Routing”.

By the numbers:

• Luna is 20 times cheaper per token, but only 12.6 times cheaper per benchmark run.
• OpenAI reports instruction hierarchy defender success of 99.97% for Sol and Luna and 99.99% for GPT-6.1 Sol.
• SonarSource found 285 vulnerabilities per million lines from GPT-6 Sol against 178 for Astra.

Key questions

Q: How should security teams implement routing for AI workloads when cost and latency vary across models?

A: Security and platform teams should use a routing layer that evaluates each request against policy, rather than hardcoding one default model.

Q: Why can a cheaper model still cost more in production than a stronger one?

A: Because task cost includes more than token price.

Q: What breaks when model safety and performance are judged only at the family level?

A: Model-family approval hides differences in tool behaviour, cyber posture and output quality between tiers.

Practitioner guidance

• Define routing rules by workload class Separate simple, repeatable tasks from multi-step agent work and route each to a default tier before developers choose a model ad hoc.
• Gate higher-tier models behind policy Require approval or policy evaluation before workloads can move from Luna to Sol or from Sol to GPT-6.1 Sol when tools or sensitive data are involved.
• Red team each model tier separately Re-test prompt injection, tool misuse and code-generation risk whenever the workload changes model or starts using a new capability such as function calling.

Bottom line: Cheaper model tiers still need explicit routing rules because task complexity, retries and escalation can erase the expected savings.

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