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Index › Performance and talent management › Goals and OKRs › Tability vs Betterworks
Goals and OKRs · October 2026 Edition

Tability vs Betterworks

Seven of fourteen models named Tability first on the direct prompt; zero named Betterworks. Tability was named by twelve of the fourteen models and Betterworks by thirteen and Tability carries 32 labels and Betterworks 26, so the shares are not directly comparable.

Tability

accepted challenger

Named in one category this edition.

Betterworks

accepted challenger

Named in six categories this edition.

First-choice share22%2%Of first choices across the direct, paraphrase, budget and scale prompts, 0 to 100.
Negative rate0%23%Negative labels as a share of the product's labels, 0 to 100.
Rank in category#2#7A position in a field of 14; printed, not drawn.
Labels3226A count; the two differ.
The two percentage rows are drawn on one 0 to 100 track, Tability reading right to left. Rank and label count are printed, not drawn.Perdoo was named alongside these two in twelve of the fourteen direct answers. Perdoo vs Tability · Perdoo vs Betterworks · Tability vs Lattice

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 goals and okrs page.

By framing

How many of the fourteen models made each the first choice, per way of asking, and how many argued against it.
TabilityFirst choices, of fourteen modelsBetterworks
Direct701 against Betterworks
Paraphrase311 against Betterworks
Comparative301 against Betterworks
Budget-constrained10
Scale-constrained10
Negative103 against Betterworks
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 Tability and Betterworks 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
Tability Betterworks first choice named as an alternative argued againstblank: not namedEach cell is one answer, Tability on the left and Betterworks on the right.

The direct prompt

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

Tability first, Betterworks not the choice

7 of 14 modelsBetterworks was named in the answer but not as the choice, or not at all.
Gemini 3.5 FlashTability alternatives: Lattice, Leapsome, Oboard, Perdoo, Profit.co
Perplexity SonarTability alternatives: Mooncamp, Perdoo
Mistral SmallPerdoo, Tability alternatives: Lattice, Mooncamp
Kimi K2Tability alternatives: Mooncamp, Perdoo, Profit.co
GLM 4.7 FlashXTability alternatives: Mooncamp, Perdoo, Profit.co
MiniMax M2.5Tability alternatives: Lattice, Mooncamp, Perdoo, Profit.co
Muse Glimmer 30BMooncamp, Tability alternatives: HiBob, Perdoo, Profit.co

Neither was the first choice, one was named

1 of 14 modelsThe answer put something else first and named one of the two as an alternative.
Claude Haiku 4.5Mooncamp alternatives: Perdoo, Profit.co, Tability

Neither was named

6 of 14 modelsThe answer made no first choice from these two in this category.
GPT-5.4 miniPerdoo alternatives: Profit.co, WorkBoard
Grok 4.1 FastLattice alternatives: Mooncamp, Profit.co, Weekdone, WorkBoard
DeepSeek V4 FlashPerdoo alternatives: Microsoft Viva Goals, Mooncamp, Profit.co
Llama 4 Maverickno first choice
Qwen 3.7 FlashMooncamp, Perdoo
GPT-6 LunaPerdoo alternatives: Lattice, Profit.co, WorkBoard

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
Tability leads by thirty points.
Tability30%#1 of 17
Betterworks0%#16 of 17
The full small business standing →
Mid-marketThe figures above
Tability leads by twenty points.
Tability22%#2 of 14
Betterworks2%#7 of 14
The full mid-market standing →
Enterprise
The order flips: Betterworks leads at enterprise.
Betterworks23%#2 of 13
Tability6%#5 of 13
The full enterprise standing →

What the models said about Tability

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

“Tability: Highly focused on simplicity, fast check-ins, and actionable tracking without enterprise bloat. Excellent automation and AI capabilities” Gemini 3.5 Flash · scale prompt · first choice
“AI goal drafting/insights, async check-ins, dashboards out-of-box, agentic OKRs. Simple UI, strong Slack/Teams. Tops benchmarks (4.5-4.7/5).” Grok 4.1 Fast · comparative prompt · first choice
“Top Pick: Tability ... start with Tability — it offers the best balance of simplicity, reporting power, and scalability at a fair price” DeepSeek V4 Flash · paraphrase prompt · first choice

What the models said about Betterworks

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

“Enterprise-heavy platforms (e.g., WorkBoard, Betterworks, Ally.io): Great for large orgs but criticized for ... Complexity: Mandatory fields overload, feature bloat” Grok 4.1 Fast · negative prompt · soft negative
“Tools like Lattice, Leapsome, Betterworks... often fall short when strategy or operations teams need a leadership cockpit.” MiniMax M2.5 · negative prompt · soft negative
“Tability and Betterworks are the top choices” Mistral Small · 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.