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Index › Equity and corporate › ESG and carbon reporting › Sweep vs Workiva
ESG and carbon reporting · October 2026 Edition

Sweep vs Workiva

Six of fourteen models named Sweep first on the direct prompt; two named Workiva. Sweep was named by twelve of the fourteen models and Workiva by thirteen and Sweep carries 23 labels and Workiva 30, so the shares are not directly comparable.

Sweep

accepted challenger

Named in one category this edition.

Workiva

criticized challenger

Named in eleven categories this edition.

First-choice share10%3%Of first choices across the direct, paraphrase, budget and scale prompts, 0 to 100.
Negative rate4%40%Negative labels as a share of the product's labels, 0 to 100.
Rank in category#2#8A position in a field of 13; printed, not drawn.
Labels2330A 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.Novata was named alongside these two in eight of the fourteen direct answers. Greenly vs Sweep · Greenly vs Workiva · Sweep vs Coolset

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 modelsWorkiva
Direct623 against Workiva
Paraphrase00
Comparative09
Budget-constrained001 against Sweep · 4 against Workiva
Scale-constrained001 against Workiva
Negative004 against Workiva
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 Workiva 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
Sweep Workiva first choice named as an alternative argued againstblank: not namedEach cell is one answer, Sweep on the left and Workiva on the right.

The direct prompt

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

Sweep first, Workiva not the choice

6 of 14 modelsWorkiva was named in the answer but not as the choice, or not at all.
Grok 4.1 FastGreenly, Sweep alternatives: Horizon ESG, cubemos
Mistral SmallSweep alternatives: EcoOnline ESG, Novata
DeepSeek V4 FlashSweep alternatives: Coolset, Greenly, Novisto
Llama 4 MaverickSweep alternatives: EcoOnline ESG, Novata
MiniMax M2.5Plan A, Sweep alternatives: EcoOnline ESG, Novata
Muse Glimmer 30BNovisto, Sweep alternatives: Coolset, Novata

Workiva first, Sweep not the choice

2 of 14 modelsSweep was named in the answer but not as the choice, or not at all.
GPT-5.4 miniWorkiva alternatives: Credibl ESG, IBM Envizi, Microsoft Cloud for Sustainability
GLM 4.7 FlashXWorkiva alternatives: Greenly, Measurabl, Novisto, Persefoni, Position Green

Neither was the first choice, one was named

5 of 14 modelsThe answer put something else first and named one of the two as an alternative.
Claude Haiku 4.5EcoOnline ESG alternatives: Coolset, Novata, Sweep
Gemini 3.5 FlashCoolset, Greenly alternatives: Gravity, KEY ESG, Novata, Sweep
Perplexity SonarGreenly alternatives: EcoOnline ESG, Novata, Novisto, Sweep
Kimi K2Novata, Position Green alternatives: Greenly, Novisto, Workiva
GPT-6 LunaGreenly alternatives: Novisto, Workiva

Neither was named

1 of 14 modelsThe answer made no first choice from these two in this category.
Qwen 3.7 FlashWatershed alternatives: Carbon Cloud, Enablon, Persefoni, PlanA, 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
Workiva leads by two points.
Workiva2%#6 of 12
Sweep0%#7 of 12
The full small business standing →
Mid-marketThe figures above
The order flips: Sweep leads at mid-market.
Sweep10%#2 of 13
Workiva3%#8 of 13
The full mid-market standing →
Enterprise
The order flips: Workiva leads at enterprise.
Workiva37%#1 of 11
Sweep2%#5 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.

“up to enterprise quotes for Sweep, IBM Envizi, and Workiva” Muse Glimmer 30B · budget prompt · soft negative
“Sweep is frequently highlighted as the best ESG reporting software for mid-market B2B companies” Mistral Small · direct prompt · first choice
“Sweep or Greenly edge out for pure mid-market B2B value based on these sources.” Grok 4.1 Fast · direct prompt · first choice
“Sweep — Best for mid-market companies building a carbon management programme” Muse Glimmer 30B · direct prompt · first choice

What the models said about Workiva

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

“Avoid paying for enterprise platforms like Workiva unless you have complex disclosure, assurance, or multi-framework requirements” Perplexity Sonar · budget prompt · hard negative
“Avoid Workiva unless you're already a public company or have a dedicated compliance team with a six-figure software budget.” DeepSeek V4 Flash · direct prompt · hard negative
“ISG's 2025 Buyers Guide named Workiva, Salesforce, and Oracle the overall leaders... A strong candidate for public companies and assurance-focused teams.” GPT-6 Luna · comparative 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.