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GRC platforms · October 2026 Edition

Drata vs LogicGate Risk Cloud

Two of fourteen models named Drata first on the direct prompt; one named LogicGate Risk Cloud. Drata was named by fourteen of the fourteen models and LogicGate Risk Cloud by ten and Drata carries 50 labels and LogicGate Risk Cloud 16, so the shares are not directly comparable.

Drata

accepted challenger

Named in seven categories this edition.

LogicGate Risk Cloud

accepted challenger

Named in four categories this edition.

First-choice share12%3%Of first choices across the direct, paraphrase, budget and scale prompts, 0 to 100.
Negative rate14%6%Negative labels as a share of the product's labels, 0 to 100.
Rank in category#4#7A position in a field of 14; printed, not drawn.
Labels5016A count; the two differ.
The two percentage rows are drawn on one 0 to 100 track, Drata reading right to left. Rank and label count are printed, not drawn.Hyperproof was named alongside these two in eleven of the fourteen direct answers. Hyperproof vs Drata · Hyperproof vs LogicGate Risk Cloud · Vanta vs Drata

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; every quote names the model and the prompt it came from. Both figures come from the GRC platforms page.

By framing

How many of the fourteen models made each the first choice, per way of asking, and how many argued against it.
DrataFirst choices, of fourteen modelsLogicGate Risk Cloud
Direct21
Paraphrase211 against LogicGate Risk Cloud
Comparative10
Budget-constrained003 against Drata
Scale-constrained30
Negative004 against Drata
Bars are first choices, 0 to 14 each sideModels that argued againstA model can name both, so the two sides of a row do not sum to fourteen.

Every model, every framing

The eighty-four answers behind the chart above, one cell each: where Drata and LogicGate Risk Cloud stood in it.
ModelDirectParaphraseComparativeBudget-constrainedScale-constrainedNegative
Claude Haiku 4.5
GPT-5.4 mini
Gemini 3.5 Flash
Perplexity Sonar
Grok 4.1 Fast
Mistral Small
DeepSeek V4 Flash
Llama 4 Maverick
Qwen 3.7 Flash
Kimi K2
GLM 4.7 FlashX
MiniMax M2.5
GPT-6 Luna
Muse Glimmer 30B
Drata LogicGate Risk Cloud first choice named as an alternative argued againstblank: not namedEach cell is one answer, Drata on the left and LogicGate Risk Cloud on the right.

The direct prompt

The plain question, one answer per model, grouped by where Drata and LogicGate Risk Cloud stood in it.

Drata first, LogicGate Risk Cloud not the choice

2 of 14 modelsLogicGate Risk Cloud was named in the answer but not as the choice, or not at all.
Claude Haiku 4.5Drata alternatives: Hyperproof, VComply, Vanta
Gemini 3.5 FlashDrata, Vanta alternatives: AuditBoard, Compyl, Hyperproof, LogicGate

LogicGate Risk Cloud first, Drata not the choice

1 of 14 modelsDrata was named in the answer but not as the choice, or not at all.
Muse Glimmer 30BLogicGate Risk Cloud alternatives: Hyperproof, Vanta, ZenGRC

Neither was the first choice, one was named

7 of 14 modelsThe answer put something else first and named one of the two as an alternative.
Grok 4.1 FastLogicGate, ZenGRC alternatives: AuditBoard, Drata, Hyperproof
DeepSeek V4 FlashHyperproof alternatives: Drata, LogicGate Risk Cloud, Vanta, ZenGRC
Qwen 3.7 FlashZenGRC alternatives: AuditBoard, Centraleyes, Drata, Vanta
Kimi K2Hyperproof, ZenGRC alternatives: Drata, Onspring, Vanta
GLM 4.7 FlashXVanta, ZenGRC alternatives: Drata, Hyperproof, LogicGate Risk Cloud
MiniMax M2.5Hyperproof alternatives: AuditBoard, LogicGate Risk Cloud
GPT-6 LunaHyperproof alternatives: Drata, Vanta

Neither was named

4 of 14 modelsThe answer made no first choice from these two in this category.
GPT-5.4 miniLogicGate alternatives: AuditBoard, Hyperproof, Optro
Perplexity SonarHyperproof alternatives: LogicGate, ZenGRC
Mistral SmallAuditBoard, ZenGRC alternatives: RiskWatch, StandardFusion, Vanta
Llama 4 Maverickno first choice

Bold names in an answer are the products the judge labeled a first choice; a model naming several gives each of them that label. The full answer text for every row is in the record.

By buyer segment

The same question asked on behalf of a different buyer. Each standing is computed within its segment and they are never added together. The figures above are the mid-market standing, which is the one the category orders by.
Small business
Drata leads by sixteen points.
Drata16%#3 of 12
LogicGate Risk Cloud0%#– of 12
The full small business standing →
Mid-marketThe figures above
Drata leads by eight points.
Drata12%#4 of 14
LogicGate Risk Cloud3%#7 of 14
The full mid-market standing →
Enterprise
Drata leads by six points.
Drata6%#5 of 13
LogicGate Risk Cloud0%#– of 13
The full enterprise standing →

What the models said about Drata

Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Two of two in this category shown.

“Avoid: Tools like Vanta, Drata, or Secureframe.” GLM 4.7 FlashX · budget prompt · hard negative
“Drata automates 90%+ of controls and starting from approximately $15,000/year, is often the best value for mid-market companies” Claude Haiku 4.5 · direct prompt · first choice

What the models said about LogicGate Risk Cloud

Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Four of five in this category shown.

“Higher price range ($25K–$150K+/year) ... Better suited for very complex enterprise risk programs” GLM 4.7 FlashX · paraphrase prompt · soft negative
“LogicGate Risk Cloud is frequently cited as an excellent choice for mid-sized companies.” Claude Haiku 4.5 · paraphrase prompt · first choice
“Frequently positioned as the mid-market / configurable workflow option.” Muse Glimmer 30B · direct prompt · first choice
“If you need deeper configurable GRC workflows with governance and risk management, LogicGate or ZenGRC are excellent choices.” DeepSeek V4 Flash · direct prompt · alternative
Also compared

Comparisons are drawn for the top eight products in each category, each against each. The output is the models' output; nothing here is a recommendation by the index.