Commissionly vs QuotaPath
Zero of twelve models named Commissionly first on the direct prompt; one named QuotaPath. Commissionly was named by eleven of the twelve models and QuotaPath by twelve and Commissionly carries 12 labels and QuotaPath 47, 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 twelve 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 sales commissions and incentive compensation page.
By framing
CommissionlyFirst choices, of twelve modelsQuotaPath
Across every category in the September 2026 Edition, Commissionly and QuotaPath were named in the same answer fifty-five times, of the 60 answers naming Commissionly and the 181 naming QuotaPath. In those answers QuotaPath took the first choice thirty-three times and Commissionly ten.
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 | | |
Commissionly QuotaPath first choice named as an alternative argued againstblank: not namedEach cell is one answer, Commissionly on the left and QuotaPath on the right.The direct prompt
QuotaPath first, Commissionly not the choice
1 of 12 modelsCommissionly was named in the answer but not as the choice, or not at all.Neither was the first choice, one was named
7 of 12 modelsThe answer put something else first and named one of the two as an alternative.Neither was named
4 of 12 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
QuotaPath54%#1 of 10Commissionly15%#2 of 10Commissionly14%#4 of 13QuotaPath4%#6 of 13QuotaPath2%#9 of 10Commissionly0%#– of 10What the models said about Commissionly
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Four of five in this category shown.
“These platforms trade flexibility for ease of use... you may quickly hit the limits” Gemini 3.5 Flash · negative prompt · soft negative
“Commissionly offers the best combination of affordability, speed of implementation, and essential features” Mistral Small · budget prompt · first choice
“For a limited budget, Commissionly and Sales Cookie stand out as the most cost-effective options” Claude Haiku 4.5 · budget prompt · first choice
“Commissionly is the most budget-oriented choice for very small teams with simple commission plans” Perplexity Sonar · budget prompt · first choice
What the models said about QuotaPath
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Five of five in this category shown.
“Be Cautious If: Your compensation structures involve complex data transformations... Lacking Calculation Depth” Gemini 3.5 Flash · negative prompt · soft negative
“Platform fee makes it ~$6K+/year for 10–20 reps (some call pricing "misleading")” Grok 4.1 Fast · budget prompt · soft negative
“Moderate Caution... reaches a ceiling as compensation plans grow in complexity” Kimi K2 · negative prompt · soft negative
“Commissionly or QuotaPath Growth offer the best balance of affordability, features, and transparent pricing.” GLM 4.7 FlashX · budget prompt · first choice
“Everstage and QuotaPath are frequently highlighted as top choices” MiniMax M2.5 · direct 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.