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ESG and carbon reporting · November 2026 Edition

Greenly vs Novisto

Two of fourteen models named Greenly first on the direct prompt; two named Novisto. Greenly was named by fourteen of the fourteen models and Novisto by nine and Greenly carries 37 labels and Novisto 13, so the shares are not directly comparable.

Greenly

accepted challenger

Named in one category this edition.

Novisto

accepted challenger

Named in one category this edition.

First-choice share24%4%Of first choices across the direct, paraphrase, budget and scale prompts, 0 to 100.
Negative rate0%8%Negative labels as a share of the product's labels, 0 to 100.
Rank in category#1#5A position in a field of 13; printed, not drawn.
Labels3713A count; the two differ.
The two percentage rows are drawn on one 0 to 100 track, Greenly reading right to left. Rank and label count are printed, not drawn.Sweep was named alongside these two in nine of the fourteen direct answers. Greenly vs Persefoni · Greenly vs Sweep · Greenly vs Watershed

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.
GreenlyFirst choices, of fourteen modelsNovisto
Direct22
Paraphrase100
Comparative00
Budget-constrained101 against Novisto
Scale-constrained00
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 Greenly and Novisto 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
Greenly Novisto first choice named as an alternative argued againstblank: not namedEach cell is one answer, Greenly on the left and Novisto on the right.

The direct prompt

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

Greenly first, Novisto not the choice

2 of 14 modelsNovisto was named in the answer but not as the choice, or not at all.
Gemini 3.5 FlashGreenly alternatives: Gravity, KEY ESG, Novata, Sweep, Watershed
DeepSeek V4 FlashGreenly, cubemos alternatives: Emerald Power, Horizon ESG, Sweep

Novisto first, Greenly not the choice

2 of 14 modelsGreenly was named in the answer but not as the choice, or not at all.
Qwen 3.7 FlashNovisto, Persefoni alternatives: ESG:ONE, Sweep, Watershed
MiniMax M2.5Novisto, Precoro ESG alternatives: IBM Envizi, Workiva ESG

Neither was the first choice, one was named

6 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
Perplexity SonarNovata alternatives: Coolset, Greenly, Novisto, Sweep
Grok 4.20Sweep alternatives: Novisto, Persefoni
Kimi K2ESG:ONE alternatives: Diligent ESG, EcoOnline ESG, Greenly
GLM 4.7 FlashXEmerald Power alternatives: Atlas Metrics, Greenly, Normative, Novato, Sweep
GPT-6 LunaSweep alternatives: Greenly, Workiva ESG

Neither was named

4 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
Muse Glimmer 30BEmerald Power alternatives: Coolset, ESG:ONE, Envoria, Normative, Sweep, cubemos

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
Greenly leads by thirty-three points.
Greenly33%#1 of 17
Novisto0%#– of 17
The full small business standing →
Mid-marketThe figures above
Greenly leads by twenty points.
Greenly24%#1 of 13
Novisto4%#5 of 13
The full mid-market standing →
Enterprise
The order flips: Novisto leads at enterprise.
Novisto2%#6 of 11
Greenly0%#– of 11
The full enterprise standing →

What the models said about Greenly

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

“Greenly has emerged as the breakout carbon accounting platform for SMEs and mid-market businesses” Claude Haiku 4.5 · paraphrase prompt · first choice
“start with Greenly or Horizon ESG for their low monthly costs and essential features” Mistral Small · budget prompt · first choice
“the most recommended carbon accounting platforms are Greenly and Coolset” Mistral Small · paraphrase prompt · first choice

What the models said about Novisto

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

“highly rated but typically require custom quotes and may be more suited to larger budgets” Mistral Small · budget prompt · soft negative
“Request demos from Persefoni (to test ease of use and cost) and Novisto (to test reporting capabilities).” Qwen 3.7 Flash · direct prompt · first choice
“I would recommend starting with Precoro ESG or Novisto based on their strong user ratings” MiniMax M2.5 · direct prompt · first choice
“Novisto is an ESG data and disclosure platform aimed at companies that need organized reporting workflows without the heaviest enterprise overhead” Claude Haiku 4.5 · direct 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.