# ModelOp Center vs Holistic AI: which do AI models recommend for AI governance, October 2026

IT AI Recommendation Index, October 2026 Edition, AI governance platforms. One of fourteen models named ModelOp Center first on the direct prompt; zero named Holistic AI. Page: https://it-ai-index.com/it-data/ai-governance-platforms/modelop-center-vs-holistic-ai/

| | First-choice share | Rank | Negative rate | Labels | Models naming it |
|---|---|---|---|---|---|
| ModelOp Center | 4% | #2 of 7 | 7% | 15 | 10 of 14 |
| Holistic AI | 2% | #4 of 7 | 23% | 22 | 11 of 14 |

## The direct prompt, model by model

- GLM 4.7 FlashX: modelop center first (first choices: ModelOp Center) (alternatives: Arthur AI, Credo AI, Fiddler AI, Guardrails AI, OneTrust AI Governance, Protect AI, ServiceNow AI Control Tower)
- GPT-5.4 mini: neither first, one named (first choices: Credo AI, OneTrust AI Governance) (alternatives: IBM watsonx.governance, ModelOp Center, SAP, ServiceNow AI Control Tower)
- Gemini 3.5 Flash: neither first, one named (first choices: Galileo, Trustible) (alternatives: Arthur, Credo AI, Fiddler AI, Holistic AI, Nightfall, ShadowLock, Strac)
- Kimi K2: neither first, one named (first choices: Montro) (alternatives: FairNow, ModelOp Center)
- MiniMax M2.5: neither first, one named (first choices: Govarna) (alternatives: ModelOp Center, Montro)
- Claude Haiku 4.5: neither named (first choices: Credo AI) (alternatives: Govern365, IBM watsonx.governance, Lumenova AI, OneTrust AI Governance)
- Perplexity Sonar: neither named (first choices: Govarna) (alternatives: Arthur, IBM watsonx.governance, OneTrust AI Governance)
- Grok 4.1 Fast: neither named (first choices: Govarna) (alternatives: Aporia, Arthur AI, Credo AI)
- Mistral Small: neither named (first choices: Govarna) (alternatives: Credo AI, Speakeasy)
- DeepSeek V4 Flash: neither named (first choices: IBM watsonx.governance, OneTrust AI Governance) (alternatives: Arthur, Drata, Fiddler AI, Vanta)
- Llama 4 Maverick: neither named (first choices: Govarna)
- Qwen 3.7 Flash: neither named (first choices: Govarna) (alternatives: Credo AI)
- GPT-6 Luna: neither named (first choices: Trustible) (alternatives: Credo AI, Microsoft Purview, OneTrust AI Governance)
- Muse Glimmer 30B: neither named (first choices: Credo AI) (alternatives: Dataiku, Fiddler AI)

## What the models said about ModelOp Center

- "not a primary runtime environment for employee LLM use, real-time prompt inspection, or operational agent controls" (Kimi K2, negative prompt, soft negative)
- "For most mid‑market B2B companies, ModelOp is the best starting point" (GLM 4.7 FlashX, direct prompt, first choice)
- "Primary Recommendation: ModelOp Center" (MiniMax M2.5, paraphrase prompt, first choice)
- "ModelOp if you want industrialized, policy-driven lifecycle automation for both ML and generative AI." (Muse Glimmer 30B, paraphrase prompt, alternative)

## What the models said about Holistic AI

- "What to avoid ... Holistic AI – starts around $40K/year for SMBs" (DeepSeek V4 Flash, budget prompt, hard negative)
- "Holistic AI | Custom quotes | No self-serve pricing" (Kimi K2, budget prompt, hard negative)
- "typically custom / enterprise pricing, often $25K-$250K+/year, and "pricing structure is less accessible for small teams"" (Muse Glimmer 30B, budget prompt, soft negative)
- "Start with a trial of Credo AI or Holistic AI if your priority is commercial compliance and customer trust." (Qwen 3.7 Flash, paraphrase prompt, first choice)
- "Pairs technical risk libraries with regulator-aligned assessment workflows; good for enterprise risk quantification" (Kimi K2, comparative prompt, alternative)
- "Best For: Organizations focused on detailed model risk management and independent auditing." (Qwen 3.7 Flash, comparative prompt, alternative)

Share is the count of first choices across the direct, paraphrase, budget and scale prompts over all fourteen models, for a mid-market B2B company; rank is within the category. Comparisons are drawn for the top eight products in each category. Published under CC BY 4.0; the output is the models' output, and nothing here is a recommendation by the index.