Two of fourteen models named Sweep first on the direct prompt; one named Workiva ESG. Both were named by all fourteen models and Sweep carries 35 labels and Workiva ESG 45, so the shares are not directly comparable.
Named in one category this edition.
Named in one category this edition.
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.
Across every category in the November 2026 Edition, Sweep and Workiva ESG were named in the same answer fifty times, of the 76 answers naming Sweep and the 140 naming Workiva ESG. In those answers Workiva ESG took the first choice eighteen times and Sweep five.
| Model | Direct | Paraphrase | Comparative | Budget-constrained | Scale-constrained | Negative |
|---|---|---|---|---|---|---|
| Claude Haiku 4.5 | ||||||
| GPT-5.4 mini | WE | WE | WE | |||
| Gemini 3.5 Flash | WE | |||||
| Perplexity Sonar | WE | WE | ||||
| Grok 4.20 | WE | WE | ||||
| Mistral Small | WE | WE | WE | WE | ||
| DeepSeek V4 Flash | WE | WE | WE | |||
| Llama 4 Maverick | WE | |||||
| Qwen 3.7 Flash | WE | WE | ||||
| Kimi K2 | ||||||
| GLM 4.7 FlashX | ||||||
| MiniMax M2.5 | WE | WE | ||||
| GPT-6 Luna | WE | |||||
| Muse Glimmer 30B | WE |
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.
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
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Six of eight in this category shown.
“What to Avoid (When on a Tight Budget) - Workiva, Sphera, IBM Envizi – Enterprise-grade platforms with heavy implementation costs” DeepSeek V4 Flash · budget prompt · hard negative
“it is recommended to avoid Workiva if you are a smaller ESG team, have a tight budget, or prioritize carbon-first reporting” Mistral Small · negative prompt · hard negative
“Avoid jumping to larger enterprise tools like Workiva unless you already know you need advanced controls” GPT-5.4 mini · budget prompt · hard negative
“If your priority is board-ready, auditable ESG reporting with strong controls, Workiva and IBM Envizi tend to stand out.” GPT-5.4 mini · comparative prompt · first choice
“Choose Workiva when the priority is controlled, auditable ESG disclosure tied to finance, legal, and investor reporting.” Perplexity Sonar · comparative prompt · first choice
“Leading platform for governed, audit-ready ESG disclosures, especially for large organizations with complex reporting needs.” Mistral Small · comparative prompt · first choice
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.