# Greenly vs Watershed: which do AI models recommend for ESG and carbon reporting, October 2026

Finance AI Recommendation Index, October 2026 Edition, ESG and carbon reporting. Four of fourteen models named Greenly first on the direct prompt; one named Watershed. Page: https://finance-ai-index.com/corporate/esg-and-carbon-reporting/greenly-vs-watershed/

| | First-choice share | Rank | Negative rate | Labels | Models naming it |
|---|---|---|---|---|---|
| Greenly | 36% | #1 of 13 | 6% | 36 | 12 of 14 |
| Watershed | 3% | #5 of 13 | 23% | 30 | 14 of 14 |

## The direct prompt, model by model

- Gemini 3.5 Flash: greenly first (first choices: Coolset, Greenly) (alternatives: Gravity, KEY ESG, Novata, Sweep)
- Perplexity Sonar: greenly first (first choices: Greenly) (alternatives: EcoOnline ESG, Novata, Novisto, Sweep)
- Grok 4.1 Fast: greenly first (first choices: Greenly, Sweep) (alternatives: Horizon ESG, cubemos)
- GPT-6 Luna: greenly first (first choices: Greenly) (alternatives: Novisto, Workiva)
- Qwen 3.7 Flash: watershed first (first choices: Watershed) (alternatives: Carbon Cloud, Enablon, Persefoni, PlanA, Sphera)
- DeepSeek V4 Flash: neither first, one named (first choices: Sweep) (alternatives: Coolset, Greenly, Novisto)
- Kimi K2: neither first, one named (first choices: Novata, Position Green) (alternatives: Greenly, Novisto, Workiva)
- GLM 4.7 FlashX: neither first, one named (first choices: Workiva) (alternatives: Greenly, Measurabl, Novisto, Persefoni, Position Green)
- Claude Haiku 4.5: neither named (first choices: EcoOnline ESG) (alternatives: Coolset, Novata, Sweep)
- GPT-5.4 mini: neither named (first choices: Workiva) (alternatives: Credibl ESG, IBM Envizi, Microsoft Cloud for Sustainability)
- Mistral Small: neither named (first choices: Sweep) (alternatives: EcoOnline ESG, Novata)
- Llama 4 Maverick: neither named (first choices: Sweep) (alternatives: EcoOnline ESG, Novata)
- MiniMax M2.5: neither named (first choices: Plan A, Sweep) (alternatives: EcoOnline ESG, Novata)
- Muse Glimmer 30B: neither named (first choices: Novisto, Sweep) (alternatives: Coolset, Novata)

## What the models said about Greenly

- "Usually not ideal on a limited budget: tools like Greenly ... can be costly for small businesses" (GPT-5.4 mini, budget prompt, soft negative)
- "High cost for smaller firms; first cycle needs heavy verification." (Grok 4.1 Fast, negative prompt, soft negative)
- "Need supported SME service with transparent pricing: Greenly. The €1,400 / $3,800 per year entry tier is the lowest published SME carbon/CSRD package in 2026." (Muse Glimmer 30B, budget prompt, first choice)
- "That makes it a good first pick when you want automated data collection, a user-friendly UI and lower total cost of ownership." (Muse Glimmer 30B, paraphrase prompt, first choice)
- "Greenly is the strongest all-around choice, offering a balance of affordability, ease of use, and robust features" (Mistral Small, paraphrase prompt, first choice)

## What the models said about Watershed

- "What to Avoid - Watershed — Excellent but typically over $50K–$250K/year; better suited for large enterprises" (Kimi K2, paraphrase prompt, hard negative)
- "rather than self-serve platforms (like Watershed, which assumes you have an in-house expert to run the strategy)" (Gemini 3.5 Flash, direct prompt, soft negative)
- "built for large corporations and carry five-figure price tags and long sales cycles" (Gemini 3.5 Flash, budget prompt, soft negative)
- "Choose Watershed or Persefoni if: Your primary immediate pain point is calculating Scope 1, 2, and 3 emissions accurately" (Qwen 3.7 Flash, comparative prompt, first choice)
- "It is the current market leader for mid-market to enterprise. It excels at automating carbon accounting" (Qwen 3.7 Flash, direct prompt, first choice)
- "I'd suggest focusing on vendors like Greenly, Novisto, Tracera, or Watershed" (MiniMax M2.5, scale prompt, first choice)

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. Comparisons are drawn for the top eight products in each category. Published under CC BY 4.0; the output is the models' output, and nothing here is a recommendation by the index.