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

Sweep vs EcoOnline ESG

Six of twelve models named Sweep first on the direct prompt; three named EcoOnline ESG. Sweep was named by eleven of the twelve models and EcoOnline ESG by nine and Sweep carries 37 labels and EcoOnline ESG 12, so the shares are not directly comparable.

Sweep

accepted challenger

Named in one category this edition.

EcoOnline ESG

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#6A position in a field of 15; printed, not drawn.
Labels3712A 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 modelsEcoOnline ESG
Direct63
Paraphrase50
Comparative00
Budget-constrained11
Scale-constrained10
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.

Every model, every framing

The seventy-two answers behind the chart above, one cell each: where Sweep and EcoOnline ESG 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 EcoOnline ESG first choice named as an alternative argued againstblank: not namedEach cell is one answer, Sweep on the left and EcoOnline ESG on the right.

The direct prompt

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

Both were the first choice

2 of 12 modelsThe answer named them together, and the judge labeled each a first choice.
Llama 4 MaverickEcoOnline ESG, Novisto, Sweep
MiniMax M2.5EcoOnline ESG, Sweep alternatives: Coolset, Normative, Novisto, Plan A

Sweep first, EcoOnline ESG an alternative

4 of 12 modelsEcoOnline ESG 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

EcoOnline ESG first, Sweep an alternative

1 of 12 modelsSweep was named in the answer but not as the choice, or not at all.
Claude Haiku 4.5EcoOnline ESG alternatives: Greenstone, Normative, Sphera, Sweep

Neither was the first choice, one was named

4 of 12 modelsThe answer put something else first and named one of the two as an alternative.
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
EcoOnline ESG0%#– of 13
The full small business standing →
Mid-marketThe figures above
Sweep leads by seventeen points.
Sweep25%#1 of 15
EcoOnline ESG8%#6 of 15
The full mid-market standing →
Enterprise
EcoOnline ESG is not named for this buyer.
Sweep6%#4 of 12
EcoOnline ESGnot named
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 EcoOnline ESG

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

“Sweep and EcoOnline appear to be the most consistently recommended options tailored to your size and needs” MiniMax M2.5 · direct prompt · first choice
“Best budget pick: EcoOnline — identified by Capterra as the "best budget option"” GPT-5.4 mini · budget prompt · first choice
“EcoOnline ESG is highlighted as best for mid-market sustainability teams” Claude Haiku 4.5 · direct 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.