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ESG and carbon reporting · November 2026 Edition

Sweep vs Coolset

Two of fourteen models named Sweep first on the direct prompt; zero named Coolset. Sweep was named by fourteen of the fourteen models and Coolset by nine and Sweep carries 35 labels and Coolset 15, so the shares are not directly comparable.

Sweep

accepted challenger

Named in one category this edition.

Coolset

accepted challenger

Named in one category this edition.

First-choice share13%2%Of first choices across the direct, paraphrase, budget and scale prompts, 0 to 100.
Negative rate3%0%Negative labels as a share of the product's labels, 0 to 100.
Rank in category#3#6A position in a field of 13; printed, not drawn.
Labels3515A count; the two differ.
The two percentage rows are drawn on one 0 to 100 track, Sweep reading right to left. Rank and label count are printed, not drawn.Greenly vs Sweep · Greenly vs Coolset · Persefoni vs Sweep

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 ESG and carbon reporting page.

By framing

How many of the fourteen models made each the first choice, per way of asking, and how many argued against it.
SweepFirst choices, of fourteen modelsCoolset
Direct20
Paraphrase31
Comparative00
Budget-constrained001 against Sweep
Scale-constrained20
Negative00
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 Sweep and Coolset stood in it.
ModelDirectParaphraseComparativeBudget-constrainedScale-constrainedNegative
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
Sweep Coolset first choice named as an alternative argued againstblank: not namedEach cell is one answer, Sweep on the left and Coolset on the right.

The direct prompt

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

Sweep first, Coolset not the choice

2 of 14 modelsCoolset was named in the answer but not as the choice, or not at all.
Grok 4.20Sweep alternatives: Novisto, Persefoni
GPT-6 LunaSweep alternatives: Greenly, Workiva ESG

Neither was the first choice, one was named

7 of 14 modelsThe answer put something else first and named one of the two as an alternative.
Claude Haiku 4.5EcoOnline ESG alternatives: Diligent ESG, Novisto, Sweep
Gemini 3.5 FlashGreenly alternatives: Gravity, KEY ESG, Novata, Sweep, Watershed
Perplexity SonarNovata alternatives: Coolset, Greenly, Novisto, Sweep
DeepSeek V4 FlashGreenly, cubemos alternatives: Emerald Power, Horizon ESG, Sweep
Qwen 3.7 FlashNovisto, Persefoni alternatives: ESG:ONE, Sweep, Watershed
GLM 4.7 FlashXEmerald Power alternatives: Atlas Metrics, Greenly, Normative, Novato, Sweep
Muse Glimmer 30BEmerald Power alternatives: Coolset, ESG:ONE, Envoria, Normative, Sweep, cubemos

Neither was named

5 of 14 modelsThe answer made no first choice from these two in this category.
GPT-5.4 miniWorkiva ESG alternatives: FigBytes, Horizon ESG, KEY ESG, Metrio
Mistral SmallEmerald Power, Horizon ESG alternatives: Metrio, Position Green
Llama 4 Maverickno first choice
Kimi K2ESG:ONE alternatives: Diligent ESG, EcoOnline ESG, Greenly
MiniMax M2.5Novisto, Precoro ESG alternatives: IBM Envizi, Workiva ESG

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
Sweep leads by two points.
Sweep4%#5 of 17
Coolset2%#10 of 17
The full small business standing →
Mid-marketThe figures above
Sweep leads by eleven points.
Sweep13%#3 of 13
Coolset2%#6 of 13
The full mid-market standing →
Enterprise
Sweep leads by four points.
Sweep4%#5 of 11
Coolset0%#– of 11
The full enterprise standing →

What the models said about Sweep

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

“~$15,000/year, good for corporate decarbonization and CSRD compliance” GLM 4.7 FlashX · budget prompt · soft negative
“Start by requesting demos from Watershed and Sweep. These two cover the vast majority of mid-sized B2B needs” Qwen 3.7 Flash · paraphrase prompt · first choice
“Often the best fit for 500 employees): *Examples:* Watershed, Sweep, Position Green, Novata, Persefoni, Greenly.” Gemini 3.5 Flash · scale prompt · first choice
“My default pick: Sweep—if you want one platform for emissions, broader ESG disclosures, and value-chain data.” GPT-6 Luna · direct prompt · first choice

What the models said about Coolset

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

“the most recommended carbon accounting platforms are Greenly and Coolset” Mistral Small · paraphrase prompt · first choice
“Coolset - Best for mid-sized companies that need structure, speed, and clarity without enterprise-level complexity.” Llama 4 Maverick · paraphrase prompt · alternative
“Best for: Mid-market companies needing structure and speed without enterprise-level complexity” GLM 4.7 FlashX · paraphrase prompt · alternative
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.