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Index › Performance and talent management › Goals and OKRs › Lattice vs Profit.co
Goals and OKRs · October 2026 Edition

Lattice vs Profit.co

One of fourteen models named Lattice first on the direct prompt; zero named Profit.co. Lattice was named by fourteen of the fourteen models and Profit.co by thirteen and Lattice carries 38 labels and Profit.co 34, so the shares are not directly comparable.

Lattice

accepted challenger

Named in nineteen categories this edition.

Profit.co

accepted challenger

Named in two categories this edition.

First-choice share13%7%Of first choices across the direct, paraphrase, budget and scale prompts, 0 to 100.
Negative rate13%9%Negative labels as a share of the product's labels, 0 to 100.
Rank in category#3#5A position in a field of 14; printed, not drawn.
Labels3834A count; the two differ.
The two percentage rows are drawn on one 0 to 100 track, Lattice 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 Lattice · Perdoo vs Profit.co · 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.
LatticeFirst choices, of fourteen modelsProfit.co
Direct10
Paraphrase60
Comparative001 against Profit.co
Budget-constrained041 against Lattice
Scale-constrained00
Negative014 against Lattice · 2 against Profit.co
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 Lattice and Profit.co 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
Lattice Profit.co first choice named as an alternative argued againstblank: not namedEach cell is one answer, Lattice on the left and Profit.co on the right.

The direct prompt

The plain question, one answer per model, grouped by where Lattice and Profit.co stood in it.

Lattice first, Profit.co an alternative

1 of 14 modelsProfit.co was named in the answer but not as the choice, or not at all.
Grok 4.1 FastLattice alternatives: Mooncamp, Profit.co, Weekdone, WorkBoard

Neither was the first choice, one was named

10 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
GPT-5.4 miniPerdoo alternatives: Profit.co, WorkBoard
Gemini 3.5 FlashTability alternatives: Lattice, Leapsome, Oboard, Perdoo, Profit.co
Mistral SmallPerdoo, Tability alternatives: Lattice, Mooncamp
DeepSeek V4 FlashPerdoo alternatives: Microsoft Viva Goals, Mooncamp, Profit.co
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
GPT-6 LunaPerdoo alternatives: Lattice, Profit.co, WorkBoard
Muse Glimmer 30BMooncamp, Tability alternatives: HiBob, Perdoo, Profit.co

Neither was named

3 of 14 modelsThe answer made no first choice from these two in this category.
Perplexity SonarTability alternatives: Mooncamp, Perdoo
Llama 4 Maverickno first choice
Qwen 3.7 FlashMooncamp, Perdoo

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
Profit.co leads by nine points.
Profit.co9%#4 of 17
Lattice0%#15 of 17
The full small business standing →
Mid-marketThe figures above
The order flips: Lattice leads at mid-market.
Lattice13%#3 of 14
Profit.co7%#5 of 14
The full mid-market standing →
Enterprise
The order flips: Profit.co leads at enterprise.
Profit.co13%#3 of 13
Lattice2%#6 of 13
The full enterprise standing →

What the models said about Lattice

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

“I wouldn’t choose Lattice on a tight budget just for OKRs: its pricing page lists an annual minimum agreement of $4,000.” GPT-6 Luna · budget prompt · hard negative
“Lattice (G2: 4.7/5 from 3,800+ reviews...) Balances OKRs with performance reviews... Great for scaling alignment in sales-driven B2B teams.” Grok 4.1 Fast · direct prompt · first choice

What the models said about Profit.co

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

“The platform feels slow, basic operations like bulk editing goals require too many clicks, the UI is cluttered” Claude Haiku 4.5 · negative prompt · soft negative
“Some reviewers note a slow, cluttered UI despite robust features.” Kimi K2 · negative prompt · soft negative
“UI can be cluttered and slower” DeepSeek V4 Flash · comparative prompt · soft negative
“Choose Profit.co if you want a dedicated OKR platform with no user limits on the free plan” Kimi K2 · budget prompt · first choice
“permanently free with unlimited OKRs and users, which makes it the strongest no-cost option” GPT-5.4 mini · budget prompt · first choice
“Best Overall (Free for up to 5 users): Profit.co ... Profit.co is the strongest option.” GLM 4.7 FlashX · 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.