Goals and OKRs · November 2026 Edition
Perdoo vs Lattice
One of fourteen models named Perdoo first on the direct prompt; zero named Lattice. Both were named by all fourteen models and Perdoo carries 52 labels and Lattice 43, so the shares are not directly comparable.
Named in one category this edition.
Named in fifteen categories this edition.
First-choice share12%10%Of first choices across the direct, paraphrase, budget and scale prompts, 0 to 100.
Negative rate12%14%Negative labels as a share of the product's labels, 0 to 100.
Rank in category#3#4A position in a field of 17; printed, not drawn.
Labels5243A count; the two differ.
The two percentage rows are drawn on one 0 to 100 track, Perdoo reading right to left. Rank and label count are printed, not drawn.Tability was named alongside these two in nine of the fourteen direct answers. Tability vs Perdoo · Tability vs Lattice · Profit.co vs Perdoo
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.
PerdooFirst choices, of fourteen modelsLattice
Direct10
Paraphrase25
Comparative201 against Lattice
Budget-constrained301 against Lattice
Scale-constrained00
Negative006 against Perdoo · 4 against Lattice
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 Perdoo and Lattice stood in it.
| Model | Direct | Paraphrase | Comparative | Budget-constrained | Scale-constrained | Negative |
|---|---|---|---|---|---|---|
| Claude Haiku 4.5 | | | | | ||
| GPT-5.4 mini | | | | |||
| Gemini 3.5 Flash | | | | | ||
| Perplexity Sonar | | | | | ||
| Grok 4.20 | | | | | | |
| 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 | | | |
Perdoo Lattice first choice named as an alternative argued againstblank: not namedEach cell is one answer, Perdoo on the left and Lattice on the right.The direct prompt
The plain question, one answer per model, grouped by where Perdoo and Lattice stood in it.
Perdoo first, Lattice an alternative
1 of 14 modelsLattice was named in the answer but not as the choice, or not at all.GPT-6 LunaPerdoo alternatives: Betterworks, Lattice, Profit.co, 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: FlowyTeam, Perdoo, Profit.co, Tability
GPT-5.4 miniBetterworks alternatives: Lattice, Leapsome, Perdoo, WorkBoard
Gemini 3.5 FlashProfit.co alternatives: Lattice, Leapsome, Microsoft Viva Goals, Quantive
Perplexity SonarCascade Strategy alternatives: Perdoo, Tability
Grok 4.20Tability alternatives: 15Five, Lattice, Leapsome
DeepSeek V4 FlashTability alternatives: 15Five, Leapsome, Perdoo, Profit.co
Kimi K2Tability alternatives: 15Five, Lattice, Perdoo, Profit.co
GLM 4.7 FlashXTability alternatives: 15Five, Perdoo, Profit.co, Weekdone
MiniMax M2.5Leapsome, Tability alternatives: 15Five, Betterworks, Lattice
Muse Glimmer 30BTability alternatives: 15Five, Betterworks, Leapsome, Perdoo, Profit.co
Neither was named
3 of 14 modelsThe answer made no first choice from these two in this category.Mistral SmallTability alternatives: 15Five, Leapsome
Llama 4 Maverickno first choice
Qwen 3.7 FlashMooncamp alternatives: 15Five, Betterworks, Leapsome
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
Perdoo leads by thirteen points.
Perdoo15%#3 of 20Lattice2%#13 of 20Mid-marketThe figures above
Enterprise
The order flips: Lattice leads at enterprise.
Lattice2%#7 of 11Perdoo0%#10 of 11What the models said about Perdoo
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Six of eight in this category shown.
“Tools like Profit and Perdoo are frequently cited in industry "graveyard" articles.” GLM 4.7 FlashX · negative prompt · hard negative
“five paid seats for Perdoo and Mooncamp, which can make "low" per-user pricing misleading for small teams” Perplexity Sonar · negative prompt · soft negative
“While popular, some users flag bugs, and some users report the platform can be buggy” Claude Haiku 4.5 · negative prompt · soft negative
“Perdoo and Profit.co are frequently cited as the best overall for mid-sized teams” Mistral Small · paraphrase prompt · first choice
“start with SugarOKR (completely free) or Perdoo (free for up to 5 users)” MiniMax M2.5 · budget prompt · first choice
“Best budget pick: Perdoo if your company has five or fewer users.” GPT-6 Luna · budget prompt · first choice
What the models said about Lattice
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. One of one in this category shown.
“Avoid enterprise tools: Skip pricier ones like Lattice, 15Five, or Quantive” Grok 4.20 · budget prompt · hard negative
Also compared
Tability vs PerdooTability vs LatticeProfit.co vs PerdooProfit.co vs LatticePerdoo vs LeapsomePerdoo vs OKRs ToolPerdoo vs MooncampPerdoo vs TeamflectLattice vs LeapsomeLattice vs OKRs ToolLattice vs MooncampLattice vs TeamflectAll twenty-eight head-to-head pages and the full goals and okrs standing
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.