Millie vs Submittable
Four of fourteen models named Millie first on the direct prompt; zero named Submittable. Millie was named by thirteen of the fourteen models and Submittable by fourteen and Millie carries 44 labels and Submittable 21, so the shares are not directly comparable.
Millie
accepted challengerNamed 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 employee giving and volunteering page.
By framing
Across every category in the November 2026 Edition, Millie and Submittable were named in the same answer twenty-three times, of the 108 answers naming Millie and the 50 naming Submittable. In those answers Submittable took the first choice three times and Millie seven.
Every model, every framing
| Model | DirectMI | ParaphraseMI | ComparativeMI | Budget-constrainedMI | Scale-constrainedMI | NegativeMI |
|---|---|---|---|---|---|---|
| Claude Haiku 4.5 | MI | MI | MI | MI | ||
| GPT-5.4 mini | MI | | MI | |||
| Gemini 3.5 Flash | MI | MI | MI | | ||
| Perplexity Sonar | MI | MI | MI | MI | ||
| Grok 4.20 | MI | | MI | MI | ||
| Mistral Small | MI | MI | MI | MI | ||
| DeepSeek V4 Flash | | MI | MI | MI | ||
| Llama 4 Maverick | ||||||
| Qwen 3.7 Flash | MI | | | MI | ||
| Kimi K2 | MI | MI | MI | |||
| GLM 4.7 FlashX | | MI | MI | |||
| MiniMax M2.5 | MI | | MI | |||
| GPT-6 Luna | MI | MI | MI | MI | MI | |
| Muse Glimmer 30B | MI | MI |
SubmittableMI first choiceMI named as an alternativeMI argued againstblank: not namedEach cell is one answer, Millie on the left and Submittable on the right.The direct prompt
Millie first, Submittable not the choice
4 of 14 modelsSubmittable was named in the answer but not as the choice, or not at all.Neither was the first choice, one was named
5 of 14 modelsThe answer put something else first and named one of the two as an alternative.Neither was named
5 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
Submittable8%#4 of 11Submittable0%#7 of 10What the models said about Millie
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Five of six in this category shown.
“These may be unsuitable where native nonprofit-CRM integration or federated/community-campaign support is essential” Perplexity Sonar · negative prompt · soft negative
“Groundswell and Millie — ask what screening they use now.” GPT-6 Luna · negative prompt · soft negative
“Millie supports donation matching programs at any budget level with customizable match ratios and caps” Claude Haiku 4.5 · budget prompt · first choice
“Uncommon Giving and Millie are the top recommendations for companies with limited budgets” Mistral Small · budget prompt · first choice
“the strongest default recommendation is Millie (formerly Groundswell)” Perplexity Sonar · paraphrase prompt · first choice
What the models said about Submittable
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Four of five in this category shown.
“it may be a poor fit for organizations needing a full employee-giving platform, payroll giving, or donor CRM” Perplexity Sonar · negative prompt · soft negative
“I'd recommend Submittable or Uncommon Giving as they offer the best combination of functionality, ease of use, and mid-market appropriate pricing” MiniMax M2.5 · paraphrase prompt · first choice
“Benevity and Submittable are the most robust and scalable options” Mistral Small · paraphrase prompt · first choice
“Submittable is my top recommendation for a mid-sized B2B company.” Grok 4.20 · paraphrase prompt · first choice
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.