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Index Sales Dialers › Allo vs Kixie
Sales dialers and calling · September 2026 Edition

Allo vs Kixie

Zero of twelve models named Allo first on the direct prompt; one named Kixie. Allo was named by eleven of the twelve models and Kixie by ten and Allo carries 12 labels and Kixie 29, so the shares are not directly comparable.

Allo

accepted challenger

Named in one category this edition.

Kixie

accepted challenger

Named in two categories this edition.

First-choice share14%5%Of first choices across the direct, paraphrase, budget and scale prompts, 0 to 100.
Negative rate0%14%Negative labels as a share of the product's labels, 0 to 100.
Rank in category#4#8A position in a field of 12; printed, not drawn.
Labels1229A count; the two differ.
The two percentage rows are drawn on one 0 to 100 track, Allo reading right to left. Rank and label count are printed, not drawn.Orum was named alongside these two in nine of the twelve direct answers. Aloware vs Allo · Aloware vs Kixie · CloudTalk vs Allo

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 dialers and calling page.

By framing

How many of the twelve models made each the first choice, per way of asking, and how many argued against it.
AlloFirst choices, of twelve modelsKixie
Direct01
Paraphrase01
Comparative01
Budget-constrained603 against Kixie
Scale-constrained00
Negative101 against Kixie
Bars are first choices, 0 to 12 each sideModels that argued againstA model can name both, so the two sides of a row do not sum to twelve.

Across every category in the September 2026 Edition, Allo and Kixie were named in the same answer eighteen times, of the 34 answers naming Allo and the 76 naming Kixie. In those answers Kixie took the first choice zero times and Allo twelve.

Every model, every framing

The seventy-two answers behind the chart above, one cell each: where Allo and Kixie 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
Allo Kixie first choice named as an alternative argued againstblank: not namedEach cell is one answer, Allo on the left and Kixie on the right.

The direct prompt

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

Kixie first, Allo not the choice

1 of 12 modelsAllo was named in the answer but not as the choice, or not at all.
Grok 4.1 FastAloware, Kixie alternatives: CloudTalk, JustCall, Nooks, Orum

Neither was the first choice, one was named

5 of 12 modelsThe answer put something else first and named one of the two as an alternative.
Gemini 3.5 FlashNooks, Orum alternatives: Aloware, Kixie, PhoneBurner
Perplexity SonarAloware alternatives: CloudTalk, JustCall, Kixie, Nooks, Orum
DeepSeek V4 FlashNooks, Orum alternatives: Aloware, JustCall, Kixie, PhoneBurner
Qwen 3.7 FlashDialer.ai alternatives: Aircall, Kixie, Outreach, Salesloft, Seismic
MiniMax M2.5Aloware alternatives: JustCall, Kixie, Orum

Neither was named

6 of 12 modelsThe answer made no first choice from these two in this category.
Claude Haiku 4.5Aloware Power Dialer, CloudTalk alternatives: Nooks, Orum, PhoneBurner, SmartDialer
GPT-5.4 miniSalesloft alternatives: Klenty, Nooks, Orum, Regie.ai
Mistral SmallAloware alternatives: CloudTalk, Nooks, Orum, Skipcall
Llama 4 MaverickAloware alternatives: Orum
Kimi K2Aloware alternatives: Aircall, Dialpad, Salesfinity
GLM 4.7 FlashXJustCall alternatives: CloudTalk, Dialpad

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
Kixie leads by two points.
Kixie16%#3 of 9
Allo14%#4 of 9
The full small business standing →
Mid-marketThe figures above
The order flips: Allo leads at mid-market.
Allo14%#4 of 12
Kixie5%#8 of 12
The full mid-market standing →
Enterprise
Allo is not named for this buyer.
Allonot named
Kixie0%#15 of 17
The full enterprise standing →

What the models said about Allo

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

“these dialers are generally more reliable: - Allo (4.7/5 on G2, single-line progressive, transparent pricing at $45/user)” DeepSeek V4 Flash · negative prompt · first choice
“Allo is the best overall value — a genuine power dialer starting at $32/user/month” DeepSeek V4 Flash · budget prompt · first choice
“Allo stands out as one of the best sales dialers (specifically a power/progressive dialer)” Grok 4.1 Fast · budget prompt · first choice

What the models said about Kixie

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

“Budget Traps to Avoid ... No published pricing; costs escalate quickly with add-ons” Kimi K2 · budget prompt · hard negative
“Avoid: ... Enterprise tools (Kixie, PhoneBurner $140+).” Grok 4.1 Fast · budget prompt · hard negative
“Many high-end dialers (like Orum or Kixie) won’t even let you sign up without booking a demo or agreeing to a multi-seat minimum.” Gemini 3.5 Flash · budget prompt · soft negative
“Kixie (G2: 4.8/5, 800+ reviews) – Best for SMB/mid-market with deep CRM glue” Grok 4.1 Fast · comparative prompt · first choice
“CRM pipeline focus, 30-60 dials/day: Kixie or Aloware.” Grok 4.1 Fast · direct prompt · first choice
“I'd recommend Kixie as the top outbound calling platform.” Grok 4.1 Fast · paraphrase 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.