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SEO and content optimization platforms · September 2026 Edition

Ubersuggest vs Frase

Zero of twelve models named Ubersuggest first on the direct prompt; zero named Frase. Ubersuggest was named by nine of the twelve models and Frase by twelve and Ubersuggest carries 15 labels and Frase 41, so the shares are not directly comparable.

Ubersuggest

accepted challenger

By Neil Patel. Named in three categories this edition.

Frase

accepted challenger

Named in three categories this edition.

First-choice share12%4%Of first choices across the direct, paraphrase, budget and scale prompts, 0 to 100.
Negative rate20%7%Negative labels as a share of the product's labels, 0 to 100.
Rank in category#3#7A position in a field of 16; printed, not drawn.
Labels1541A count; the two differ.
The two percentage rows are drawn on one 0 to 100 track, Ubersuggest reading right to left. Rank and label count are printed, not drawn.Surfer SEO was named alongside these two in ten of the twelve direct answers. Surfer SEO vs Ubersuggest · Surfer SEO vs Frase · Semrush vs Ubersuggest

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 SEO and content optimization platforms page.

By framing

How many of the twelve models made each the first choice, per way of asking, and how many argued against it.
UbersuggestFirst choices, of twelve modelsFrase
Direct00
Paraphrase00
Comparative00
Budget-constrained62
Scale-constrained00
Negative013 against Ubersuggest · 3 against Frase
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, Ubersuggest and Frase were named in the same answer seventeen times, of the 40 answers naming Ubersuggest and the 113 naming Frase. In those answers Frase took the first choice four times and Ubersuggest four.

Every model, every framing

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

The direct prompt

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

Neither was the first choice, one was named

2 of 12 modelsThe answer put something else first and named one of the two as an alternative.
Claude Haiku 4.5Sight AI alternatives: Intero Digital, Stratabeat, Ubersuggest, Virayo, Writesonic
Grok 4.1 FastSurfer SEO alternatives: Ahrefs, Clearscope, Frase, MarketMuse, Semrush

Neither was named

10 of 12 modelsThe answer made no first choice from these two in this category.
GPT-5.4 miniSemrush alternatives: Ahrefs, Clearscope, Conductor
Gemini 3.5 FlashSemrush, Surfer SEO alternatives: Ahrefs, Clearscope, SE Ranking
Perplexity SonarSemrush alternatives: Ahrefs, Clearscope, Surfer SEO
Mistral SmallHubSpot Content Hub, HubSpot Marketing Hub alternatives: Clearscope, MarketMuse, Semrush, Surfer SEO
DeepSeek V4 FlashSemrush alternatives: Ahrefs, Clearscope, MarketMuse, Surfer SEO
Llama 4 MaverickKeygrip alternatives: Ahrefs, Clearscope, Screaming Frog, Semrush, Surfer SEO
Qwen 3.7 FlashAhrefs, Semrush alternatives: Clearscope, HubSpot, SE Ranking, Screaming Frog, Sitebulb, Surfer SEO
Kimi K2Semrush alternatives: Ahrefs, Clearscope, MarketMuse, Screaming Frog, Surfer SEO
GLM 4.7 FlashXSemrush alternatives: Ahrefs, Clearscope, NeuronWriter, Surfer SEO
MiniMax M2.5Surfer SEO alternatives: Ahrefs, MarketMuse

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
Frase leads by ten points.
Frase15%#3 of 13
Ubersuggest6%#7 of 13
The full small business standing →
Mid-marketThe figures above
The order flips: Ubersuggest leads at mid-market.
Ubersuggest12%#3 of 16
Frase4%#7 of 16
The full mid-market standing →
Enterprise
Level: the same share of first choices.
Ubersuggest0%#– of 13
Frase0%#12 of 13
The full enterprise standing →

What the models said about Ubersuggest

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

“Ubersuggest | 42/100 (High) | Persistent quality complaints; often criticized for outdated features” GLM 4.7 FlashX · negative prompt · hard negative
“Persistent data quality complaints ... Don't make strategic decisions based on its data alone.” DeepSeek V4 Flash · negative prompt · soft negative
“Persistent quality complaints; data accuracy issues | Moderate” Kimi K2 · negative prompt · soft negative
“I’d pick Ubersuggest for most budget-conscious companies because it gives the broadest useful feature set at a relatively low entry price” Perplexity Sonar · budget prompt · first choice
“Ubersuggest stands out as the top overall pick for most small businesses needing both SEO and content optimization under $30/month” Grok 4.1 Fast · budget prompt · first choice
“My top recommendation: Start with Ubersuggest ($29/month) if you need keyword research and competitor analysis” Mistral Small · budget prompt · first choice

What the models said about Frase

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

“Frase - Low-cost option with user reports of inaccurate recommendations” Mistral Small · negative prompt · hard negative
“Criticized as "dead" in 2026—doesn't account for LLMs” GLM 4.7 FlashX · negative prompt · hard negative
“excellent tools when used correctly, but they are highly dangerous when misused” Gemini 3.5 Flash · negative prompt · soft negative
“Frase gives you content briefs and optimization at a fraction of the cost... it offers the most functionality per dollar” Claude Haiku 4.5 · budget prompt · first choice
“Frase is the best starting point for most small companies” GPT-5.4 mini · budget prompt · first choice
“Budget-conscious | Frase | $15/month” Kimi K2 · negative 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.