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Index › Partner and channel › Referrals › PartnerStack vs Friendbuy
Referral and partner programs · October 2026 Edition

PartnerStack vs Friendbuy

One of fourteen models named PartnerStack first on the direct prompt; one named Friendbuy. Both were named by all fourteen models and PartnerStack carries 30 labels and Friendbuy 23, so the shares are not directly comparable.

PartnerStack

accepted challenger

Named in five categories this edition.

Friendbuy

accepted challenger

Palos Verdes Estates, United States, founded 2010. Named in two categories this edition.

First-choice share22%4%Of first choices across the direct, paraphrase, budget and scale prompts, 0 to 100.
Negative rate0%9%Negative labels as a share of the product's labels, 0 to 100.
Rank in category#1#7A position in a field of 15; printed, not drawn.
Labels3023A count; the two differ.
The two percentage rows are drawn on one 0 to 100 track, PartnerStack reading right to left. Rank and label count are printed, not drawn.Referral Rock was named alongside these two in thirteen of the fourteen direct answers. PartnerStack vs Referral Rock · PartnerStack vs Smile.io · PartnerStack vs GrowSurf

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 referral and partner programs page.

By framing

How many of the fourteen models made each the first choice, per way of asking, and how many argued against it.
PartnerStackFirst choices, of fourteen modelsFriendbuy
Direct11
Paraphrase110
Comparative01
Budget-constrained00
Scale-constrained01
Negative002 against Friendbuy
Bars are first choices, 0 to 14 each sideModels that argued againstA model can name both, so the two sides of a row do not sum to fourteen.

Every model, every framing

The eighty-four answers behind the chart above, one cell each: where PartnerStack and Friendbuy stood in it.
ModelDirectParaphraseComparativeBudget-constrainedScale-constrainedNegative
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
PartnerStack Friendbuy first choice named as an alternative argued againstblank: not namedEach cell is one answer, PartnerStack on the left and Friendbuy on the right.

The direct prompt

The plain question, one answer per model, grouped by where PartnerStack and Friendbuy stood in it.

PartnerStack first, Friendbuy not the choice

1 of 14 modelsFriendbuy was named in the answer but not as the choice, or not at all.
Qwen 3.7 FlashPartnerStack alternatives: Cello.so, Partnero

Friendbuy first, PartnerStack not the choice

1 of 14 modelsPartnerStack was named in the answer but not as the choice, or not at all.
Llama 4 MaverickFriendbuy alternatives: Partnero, Referral Rock, SaaSquatch

Neither was the first choice, one was named

9 of 14 modelsThe answer put something else first and named one of the two as an alternative.
Claude Haiku 4.5Cello alternatives: Friendbuy, PartnerStack, Referral Rock
GPT-5.4 miniReferral Factory alternatives: Ambassador, PartnerStack, Referral Rock, impact.com
Gemini 3.5 FlashReferral Rock alternatives: GrowSurf, PartnerStack, Referral Factory, impact.com Advocate
Grok 4.1 FastAmbassador alternatives: PartnerStack, Referral Rock
DeepSeek V4 FlashCello, Referral Rock alternatives: Ambassador, GrowSurf, PartnerStack
Kimi K2Referral Rock alternatives: FirstPromoter, PartnerStack
MiniMax M2.5Referral Rock alternatives: Ambassador, Friendbuy, PartnerStack
GPT-6 LunaSaaSquatch alternatives: PartnerStack, Referral Rock
Muse Glimmer 30BAmbassador alternatives: Extole, PartnerStack, Partnerize, Referral Rock

Neither was named

3 of 14 modelsThe answer made no first choice from these two in this category.
Perplexity SonarReferral Rock alternatives: Ambassador, CustomerGauge, GrowSurf, Referral Factory
Mistral SmallReferral Rock alternatives: SaaSquatch
GLM 4.7 FlashXCello alternatives: Ambassador, Extole, Referral Factory, Referral Rock

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

The same question asked on behalf of a different buyer. Each standing is computed within its segment and they are never added together. The figures above are the mid-market standing, which is the one the category orders by.
Small business
PartnerStack leads by thirteen points.
PartnerStack13%#2 of 10
Friendbuy0%#10 of 10
The full small business standing →
Mid-marketThe figures above
PartnerStack leads by nineteen points.
PartnerStack22%#1 of 15
Friendbuy4%#7 of 15
The full mid-market standing →
Enterprise
PartnerStack leads by seven points.
PartnerStack13%#4 of 12
Friendbuy6%#5 of 12
The full enterprise standing →

What the models said about PartnerStack

Every negative label with a quote, up to three, then the highest-weighted positives, up to three. One of one in this category shown.

“PartnerStack - a full-lifecycle partner management platform that allows companies to build, track, and scale partner, affiliate, and reseller programs in one place.” Llama 4 Maverick · paraphrase prompt · first choice

What the models said about Friendbuy

Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Three of three in this category shown.

“Use Referral Factory or Friendbuy if you want a customer referral program that is relatively easy to launch and optimize.” Perplexity Sonar · comparative prompt · first choice
“Friendbuy - Best for mid-market and enterprise eCommerce brands that want customization and testing.” Llama 4 Maverick · direct prompt · first choice
“Popular picks like Friendbuy or Talkable excel for enterprises” Grok 4.1 Fast · scale prompt · first choice
Also compared

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.