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Video interviewing · October 2026 Edition

Willo vs Hireflix

Zero of fourteen models named Willo first on the direct prompt; zero named Hireflix. Willo was named by thirteen of the fourteen models and Hireflix by thirteen and Willo carries 39 labels and Hireflix 34, so the shares are not directly comparable.

Willo

accepted challenger

Named in one category this edition.

Hireflix

accepted challenger

Named in two categories this edition.

First-choice share8%6%Of first choices across the direct, paraphrase, budget and scale prompts, 0 to 100.
Negative rate3%3%Negative labels as a share of the product's labels, 0 to 100.
Rank in category#2#3A position in a field of 9; printed, not drawn.
Labels3934A count; the two differ.
The two percentage rows are drawn on one 0 to 100 track, Willo reading right to left. Rank and label count are printed, not drawn.Spark Hire was named alongside these two in fourteen of the fourteen direct answers. Spark Hire vs Willo · Spark Hire vs Hireflix · Willo vs Hirevire

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 video interviewing page.

By framing

How many of the fourteen models made each the first choice, per way of asking, and how many argued against it.
WilloFirst choices, of fourteen modelsHireflix
Direct00
Paraphrase301 against Hireflix
Comparative00
Budget-constrained13
Scale-constrained00
Negative211 against Willo
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.

Across every category in the October 2026 Edition, Willo and Hireflix were named in the same answer seventy-five times, of the 115 answers naming Willo and the 101 naming Hireflix. In those answers Hireflix took the first choice twenty-nine times and Willo six.

Every model, every framing

The eighty-four answers behind the chart above, one cell each: where Willo and Hireflix 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
Willo Hireflix first choice named as an alternative argued againstblank: not namedEach cell is one answer, Willo on the left and Hireflix on the right.

The direct prompt

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

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.
Gemini 3.5 FlashSpark Hire alternatives: BrightHire, Metaview, VidCruiter, Willo
Grok 4.1 FastSpark Hire alternatives: Hireflix, VidCruiter, Willo
DeepSeek V4 FlashSpark Hire alternatives: Willo
Kimi K2Spark Hire, interviewstream alternatives: Hireflix, VidCruiter
GLM 4.7 FlashXSpark Hire alternatives: Hireflix, Willo

Neither was named

9 of 14 modelsThe answer made no first choice from these two in this category.
Claude Haiku 4.5Spark Hire alternatives: HackerRank
GPT-5.4 miniSpark Hire alternatives: HireVue, VidCruiter
Perplexity SonarSpark Hire alternatives: Rework, VidCruiter
Mistral SmallSpark Hire alternatives: Breezy HR, VidCruiter
Llama 4 MaverickSpark Hire alternatives: VidCruiter
Qwen 3.7 FlashHireVue alternatives: Modern Hire, Spark Hire, Talmatic, VidCruiter
MiniMax M2.5Spark Hire alternatives: VidCruiter, interviewstream
GPT-6 LunaSpark Hire alternatives: HireVue, VidCruiter
Muse Glimmer 30BSpark Hire alternatives: Breezy, VidCruiter

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
Hireflix leads by thirty-one points.
Hireflix43%#1 of 11
Willo12%#3 of 11
The full small business standing →
Mid-marketThe figures above
The order flips: Willo leads at mid-market.
Willo8%#2 of 9
Hireflix6%#3 of 9
The full mid-market standing →
Enterprise
The order flips: Hireflix leads at enterprise.
Hireflix6%#4 of 6
Willo0%#5 of 6
The full enterprise standing →

What the models said about Willo

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

“Willo doesn't support live video interviews or screen sharing, and lacks a mobile app” Claude Haiku 4.5 · negative prompt · soft negative
“I'd choose Willo Lite for a limited budget because it combines *low cost*, *clear pricing*, and *no long-term commitment*” Perplexity Sonar · budget prompt · first choice
“Look for highly transparent, candidate-first platforms (like Willo or VidCruiter) that allow retakes” Gemini 3.5 Flash · negative prompt · first choice
“Willo or AsyncInterview are excellent choices due to their ease of use, strong integration options” Mistral Small · paraphrase prompt · first choice

What the models said about Hireflix

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

“very bare-bones — best for small teams / solo recruiters, not mid-sized orgs” DeepSeek V4 Flash · paraphrase prompt · hard negative
“Hireflix at a flat $75 a month with unlimited interviews is the strongest fit for most small teams.” Muse Glimmer 30B · budget prompt · first choice
“tools like Willo, Hireflix, VidCruiter, or Braintrust AIR, which get better candidate feedback” Grok 4.1 Fast · negative prompt · first choice
“Top Overall Pick for Startups/SMBs: Hireflix” Qwen 3.7 Flash · budget 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.