# FirmRoom vs Datasite Diligence: which do AI models recommend for virtual data rooms, October 2026

Finance AI Recommendation Index, October 2026 Edition, Virtual data rooms. One of fourteen models named FirmRoom first on the direct prompt; zero named Datasite Diligence. Page: https://finance-ai-index.com/corporate/virtual-data-rooms/firmroom-vs-datasite-diligence/

| | First-choice share | Rank | Negative rate | Labels | Models naming it |
|---|---|---|---|---|---|
| FirmRoom | 10% | #4 of 15 | 5% | 22 | 12 of 14 |
| Datasite Diligence | 3% | #8 of 15 | 47% | 53 | 14 of 14 |

## The direct prompt, model by model

- Qwen 3.7 Flash: firmroom first (first choices: FirmRoom, Firmex) (alternatives: iDeals)
- GPT-5.4 mini: neither first, one named (first choices: iDeals Virtual Data Room) (alternatives: Clinked, Datasite Diligence, Firmex, SecureDocs)
- Perplexity Sonar: neither first, one named (first choices: Firmex) (alternatives: Datasite Diligence, Papermark, SecureDocs, iDeals)
- Grok 4.1 Fast: neither first, one named (first choices: Firmex, iDeals) (alternatives: FirmRoom, SecureDocs, ShareVault)
- Mistral Small: neither first, one named (first choices: Firmex, iDeals) (alternatives: FirmRoom)
- Kimi K2: neither first, one named (first choices: iDeals) (alternatives: DealRoom, FirmRoom, Firmex)
- MiniMax M2.5: neither first, one named (first choices: iDeals) (alternatives: FirmRoom, Firmex)
- GPT-6 Luna: neither first, one named (first choices: Firmex) (alternatives: Datasite Diligence, DealRoom, Intralinks, iDeals)
- Muse Glimmer 30B: neither first, one named (first choices: iDeals) (alternatives: DealRoom, FirmRoom, Firmex)
- Claude Haiku 4.5: neither named (first choices: iDeals) (alternatives: CapLinked, Firmex)
- Gemini 3.5 Flash: neither named (first choices: iDeals) (alternatives: CapLinked, DealRoom, Firmex, ShareVault)
- DeepSeek V4 Flash: neither named (first choices: iDeals) (alternatives: Firmex, SecureDocs)
- Llama 4 Maverick: neither named
- GLM 4.7 FlashX: neither named (first choices: iDeals Virtual Data Room) (alternatives: Clinked, DealRoom, Firmex)

## What the models said about FirmRoom

- "FirmRoom has a polarized reputation. While praised for ease of use, there are specific technical complaints to watch for." (Qwen 3.7 Flash, negative prompt, soft negative)
- "The mid-market leaders (iDeals, FirmEx, FirmRoom, SecureDocs, Papermark) offer strong security and features at flat-rate pricing" (DeepSeek V4 Flash, scale prompt, first choice)
- "For a mid-sized B2B company, I'd recommend FirmRoom for its balance of price, ease of use, and comprehensive features." (GLM 4.7 FlashX, paraphrase prompt, first choice)
- "Start with Firmex if you do multiple deals a year, or FirmRoom if you value simplicity and flat-rate pricing." (Qwen 3.7 Flash, direct prompt, first choice)

## What the models said about Datasite Diligence

- "What to Avoid ... Enterprise providers like Datasite or Intralinks: $5,000–$50,000+ per deal" (Kimi K2, budget prompt, hard negative)
- "Avoid legacy per-page pricing (Intralinks, Datasite) unless doing large cross-border deals." (Kimi K2, direct prompt, hard negative)
- "Avoid legacy providers like Datasite and Intralinks" (DeepSeek V4 Flash, budget prompt, hard negative)
- "Built around M&A workflows, with AI-assisted document search and review, redaction, Q&A, and deal tools. A strong candidate when handling a large room or many bidders." (GPT-6 Luna, comparative prompt, first choice)
- "Choose Intralinks/Datasite if: You're working on a large M&A deal where your counterparty (investment bank) mandates it" (Kimi K2, comparative prompt, first choice)
- "Best for large enterprise M&A and complex, high-value transactions... considered the enterprise standard for M&A" (Mistral Small, comparative prompt, first choice)

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.