Breezing vs Cryptio
Zero of fourteen models named Breezing first on the direct prompt; two named Cryptio. Breezing was named by eleven of the fourteen models and Cryptio by fourteen and Breezing carries 19 labels and Cryptio 43, 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 crypto accounting page.
By framing
BreezingFirst choices, of fourteen modelsCryptio
Across every category in the October 2026 Edition, Breezing and Cryptio were named in the same answer forty times, of the 67 answers naming Breezing and the 137 naming Cryptio. In those answers Cryptio took the first choice two times and Breezing twenty-one.
Every model, every framing
| Model | Direct | Paraphrase | Comparative | Budget-constrained | Scale-constrained | Negative |
|---|---|---|---|---|---|---|
| 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 | | | | |
Breezing Cryptio first choice named as an alternative argued againstblank: not namedEach cell is one answer, Breezing on the left and Cryptio on the right.The direct prompt
Cryptio first, Breezing not the choice
2 of 14 modelsBreezing was named in the answer but not as the choice, or not at all.Neither was the first choice, one was named
7 of 14 modelsThe answer put something else first and named one of the two as an alternative.Neither was named
5 of 14 modelsThe answer made no first choice from these two in this category.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
Breezing47%#1 of 12Cryptio2%#10 of 12Cryptio14%#2 of 11Breezing6%#– of 11What the models said about Breezing
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Three of four in this category shown.
“I'd recommend Breezing, which targets small-to-midsize businesses with published pricing from $29 to $2,917 per month” Claude Haiku 4.5 · paraphrase prompt · first choice
“Breezing (Best Overall Budget Subledger) ... widely considered the most cost-effective, dedicated crypto subledger” Gemini 3.5 Flash · budget prompt · first choice
“For the most budget-conscious choice, Breezing or Koinly's free tier would be ideal starting points.” Claude Haiku 4.5 · budget prompt · first choice
What the models said about Cryptio
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 on a Tight Budget (Enterprise tools) - Cryptio (starts ~$449/mo)” DeepSeek V4 Flash · budget prompt · hard negative
“Cryptio (starting at ~$449/month)—are designed for enterprises and are far too expensive for startups or small-to-medium businesses” Gemini 3.5 Flash · budget prompt · soft negative
“typically start at higher price points (often $49/mo+ or enterprise-only contracts)” Qwen 3.7 Flash · budget prompt · soft negative
“Enterprise-grade subledgers like Bitwave or Cryptio, which offer audit support, DeFi classification, and ERP integrations.” Mistral Small · negative prompt · first choice
“Use an enterprise sub-ledger like Cryptio, Bitwave, Lukka, Ledgible or TRES when you need GAAP/IFRS journal entries” Muse Glimmer 30B · comparative prompt · first choice
“Choose Ledgible or Cryptio if: You run a business, hold significant assets, need to reconcile accounts monthly” Qwen 3.7 Flash · 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.