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Index Equity and corporate ESG and carbon reporting › Sweep vs Coolset
ESG and carbon reporting · September 2026 Edition

Sweep vs Coolset

Six of twelve models named Sweep first on the direct prompt; zero named Coolset. Sweep was named by eleven of the twelve models and Coolset by ten and Sweep carries 37 labels and Coolset 19, 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 share25%8%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#1#5A position in a field of 15; printed, not drawn.
Labels3719A 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.Novisto was named alongside these two in eight of the twelve direct answers. Sweep vs Greenly · Sweep vs Novisto · Sweep vs Plan A

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 ESG and carbon reporting page.

By framing

How many of the twelve models made each the first choice, per way of asking, and how many argued against it.
SweepFirst choices, of twelve modelsCoolset
Direct60
Paraphrase52
Comparative00
Budget-constrained10
Scale-constrained12
Negative001 against Sweep
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, Sweep and Coolset were named in the same answer twenty times, of the 73 answers naming Sweep and the 36 naming Coolset. In those answers Coolset took the first choice one time and Sweep six.

Every model, every framing

The seventy-two 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 4.1 Fast
Mistral Small
DeepSeek V4 Flash
Llama 4 Maverick
Qwen 3.7 Flash
Kimi K2
GLM 4.7 FlashX
MiniMax M2.5
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 an alternative

6 of 12 modelsCoolset was named in the answer but not as the choice, or not at all.
Gemini 3.5 FlashGreenly, Sweep alternatives: Coolset, Novata
Grok 4.1 FastSweep alternatives: Coolset, Novisto
Mistral SmallSweep alternatives: Coolset, EcoOnline ESG
DeepSeek V4 FlashSweep alternatives: Coolset, Greenly, Plan A, Tanso
Llama 4 MaverickEcoOnline ESG, Novisto, Sweep
MiniMax M2.5EcoOnline ESG, Sweep alternatives: Coolset, Normative, Novisto, Plan A

Neither was the first choice, one was named

5 of 12 modelsThe answer put something else first and named one of the two as an alternative.
Claude Haiku 4.5EcoOnline ESG alternatives: Greenstone, Normative, Sphera, Sweep
Perplexity SonarNovisto alternatives: EcoOnline ESG, Greenly, Novata, Sweep
Qwen 3.7 FlashNovisto alternatives: Gravity, LogicGate, Sweep
Kimi K2Novisto alternatives: Coolset, Sustain.Life, Sweep, Workiva
GLM 4.7 FlashXNovisto alternatives: EcoOnline ESG, Greenly, Sustain.Life, Sweep

Neither was named

1 of 12 modelsThe answer made no first choice from these two in this category.
GPT-5.4 miniWorkiva alternatives: IBM Envizi, Novisto, Sphera

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
Level: the same share of first choices.
Sweep0%#8 of 13
Coolset0%#7 of 13
The full small business standing →
Mid-marketThe figures above
Sweep leads by seventeen points.
Sweep25%#1 of 15
Coolset8%#5 of 15
The full mid-market standing →
Enterprise
Sweep leads by six points.
Sweep6%#4 of 12
Coolset0%#– of 12
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.

“some unproven mid-market carbon tools like Sweep, Plan A... lack robust data governance” Grok 4.1 Fast · negative prompt · soft negative
“For most mid-market B2B companies, Sweep offers the strongest balance of supply chain support, framework coverage, and mid-market-appropriate pricing.” DeepSeek V4 Flash · direct prompt · first choice
“Sweep or Plan A are excellent choices... If you are in Europe and require CSRD alignment, Sweep is highly recommended.” Mistral Small · paraphrase prompt · first choice
“Sweep and EcoOnline appear to be the most consistently recommended options tailored to your size and needs” MiniMax M2.5 · 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.

“Coolset is frequently cited as the "go-to" for mid-market companies... Choose Coolset if you are in Europe and need strict regulatory compliance (CSRD)” Qwen 3.7 Flash · paraphrase prompt · first choice
“Prioritize platforms suited for 500–5,000 employees, like Coolset, ESG:ONE, EcoOnline, or Novisto... Shortlist 3–5: Coolset (multi-framework, AI)” Grok 4.1 Fast · scale prompt · first choice
“Sweep / Coolset / Plan A / ESG:ONE: These are specifically built for upper-mid-market companies.” Gemini 3.5 Flash · scale 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.