Firmex vs Ansarada
Five of fourteen models named Firmex first on the direct prompt; zero named Ansarada. Firmex was named by fourteen of the fourteen models and Ansarada by eleven and Firmex carries 52 labels and Ansarada 21, so the shares are not directly comparable.
Named in one category this edition.
Named in one category this edition.
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 virtual data rooms page.
By framing
FirmexFirst choices, of fourteen modelsAnsarada
Across every category in the October 2026 Edition, Firmex and Ansarada were named in the same answer forty-four times, of the 118 answers naming Firmex and the 57 naming Ansarada. In those answers Ansarada took the first choice zero times and Firmex one.
Every model, every framing
| Model | Direct | Paraphrase | Comparative | Budget-constrained | Scale-constrained | Negative |
|---|---|---|---|---|---|---|
| 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 | | | |
Firmex Ansarada first choice named as an alternative argued againstblank: not namedEach cell is one answer, Firmex on the left and Ansarada on the right.The direct prompt
Firmex first, Ansarada not the choice
5 of 14 modelsAnsarada was named in the answer but not as the choice, or not at all.Neither was the first choice, one was named
8 of 14 modelsThe answer put something else first and named one of the two as an alternative.Neither was named
1 of 14 modelsThe answer made no first choice from these two in this category.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
What the models said about Firmex
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Five of six in this category shown.
“Quote-only pricing (Firmex): Hidden fees and unpredictable costs” Kimi K2 · budget prompt · hard negative
“the enterprise provider Datasite owns both Firmex and Ansarada” Gemini 3.5 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
“Firmex and iDeals are the top recommendations due to their strong feature sets, scalability, and mid-market focus” Mistral Small · direct 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 Ansarada
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Five of six in this category shown.
“One concrete example to examine carefully: Ansarada’s storage-overage terms. ... That’s a pricing and contract caution—not a claim that the product is unsafe.” GPT-6 Luna · negative prompt · soft negative
“Watch out for "peak usage" storage clauses (such as those in Ansarada's pricing)” Gemini 3.5 Flash · negative prompt · soft negative
“Modern, Scalable Mid-Market (Strongest fit for a 500-person firm): Examples: iDeals, Firmex, Ansarada.” Gemini 3.5 Flash · scale prompt · first choice
“my default recommendation would be Ansarada” GPT-5.4 mini · paraphrase prompt · first choice
“Ansarada is noted for "AI-supported deal workflows, M&A, capital raising, infrastructure procurement, and structured diligence processes"” Muse Glimmer 30B · comparative prompt · alternative
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.