FaceUp vs AllVoices
Seven of fourteen models named FaceUp first on the direct prompt; zero named AllVoices. FaceUp was named by twelve of the fourteen models and AllVoices by nine and FaceUp carries 33 labels and AllVoices 15, so the shares are not directly comparable.
Named in one category this edition.
Named in two categories 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 whistleblowing and investigations page.
By framing
FaceUpFirst choices, of fourteen modelsAllVoices
Across every category in the October 2026 Edition, FaceUp and AllVoices were named in the same answer twenty-three times, of the 95 answers naming FaceUp and the 36 naming AllVoices. In those answers AllVoices took the first choice two times and FaceUp eight.
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 | | | | |
FaceUp AllVoices first choice named as an alternative argued againstblank: not namedEach cell is one answer, FaceUp on the left and AllVoices on the right.The direct prompt
FaceUp first, AllVoices an alternative
7 of 14 modelsAllVoices was named in the answer but not as the choice, or not at all.Neither was the first choice, one was named
3 of 14 modelsThe answer put something else first and named one of the two as an alternative.Neither was named
4 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
FaceUp23%#1 of 10AllVoices3%#8 of 10FaceUp25%#1 of 12AllVoices4%#7 of 12What the models said about FaceUp
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Three of four in this category shown.
“I'd recommend FaceUp as the primary choice — it hits the sweet spot of affordability, quick deployment, strong anonymity guarantees, and built-in case management” DeepSeek V4 Flash · paraphrase prompt · first choice
“This platform is frequently highlighted for its ability to integrate hotline intake, triage actions, and investigator notes into a single case record.” Mistral Small · paraphrase prompt · first choice
“FaceUp stands out as the top choice due to its strong mid-market focus, comprehensive investigation tools, and positive user feedback” Mistral Small · direct prompt · first choice
What the models said about AllVoices
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Three of three in this category shown.
“For a standard, tech-forward mid-sized B2B company, AllVoices is the most well-rounded option to build a positive culture of trust.” Gemini 3.5 Flash · paraphrase prompt · first choice
“Top Recommendation: AllVoices ... For most mid-sized B2B companies, I'd start with AllVoices.” Kimi K2 · paraphrase prompt · first choice
“Consider it when employee accessibility and HR workflows are central; validate whether its controls and compliance capabilities fit your program.” GPT-6 Luna · 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.