Aloware vs Aircall
Six of twelve models named Aloware first on the direct prompt; zero named Aircall. Aloware was named by ten of the twelve models and Aircall by twelve and Aloware carries 27 labels and Aircall 29, so the shares are not directly comparable.
Named in one category this edition.
By Q109016663, Paris, founded 2014. Named in two categories this edition.
Share is the count of first choices across the direct, paraphrase, budget and scale prompts over all twelve 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 sales dialers and calling page.
By framing
AlowareFirst choices, of twelve modelsAircall
Across every category in the September 2026 Edition, Aloware and Aircall were named in the same answer twenty-one times, of the 66 answers naming Aloware and the 85 naming Aircall. In those answers Aircall took the first choice zero times and Aloware nine.
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 | | | |
Aloware Aircall first choice named as an alternative argued againstblank: not namedEach cell is one answer, Aloware on the left and Aircall on the right.The direct prompt
Aloware first, Aircall an alternative
6 of 12 modelsAircall was named in the answer but not as the choice, or not at all.Neither was the first choice, one was named
3 of 12 modelsThe answer put something else first and named one of the two as an alternative.Neither was named
3 of 12 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
Aloware18%#1 of 12Aircall7%#7 of 12What the models said about Aloware
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Three of four in this category shown.
“Aloware stands out as the only platform combining enterprise AI, unlimited calling, deep CRM sync, and spam protection without enterprise pricing—making it the top choice” Kimi K2 · comparative prompt · first choice
“Aloware offers the best combination of scalability, unlimited calling, deep CRM integration, and compliance features, making it the safest choice for 2025.” Mistral Small · direct prompt · first choice
“The best sales dialer for a mid-market B2B company is Aloware, as it ranked #1 in a 90-day testing across all 6 criteria” Llama 4 Maverick · direct prompt · first choice
What the models said about Aircall
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Six of eight in this category shown.
“Biggest concerns: Aggressive auto-renewal, unreliable call logging, and poor outbound dialing features.” DeepSeek V4 Flash · negative prompt · hard negative
“Aircall's power dialer needs the $70 Professional plan, not the $30 Essentials plan” DeepSeek V4 Flash · budget prompt · soft negative
“Easy setup and strong integrations, but less focused on high-concurrency dialing” Perplexity Sonar · comparative prompt · soft negative
“my default recommendation would be Aircall if you want the best balance of ease of use, CRM integration, and fast rollout” GPT-5.4 mini · paraphrase prompt · first choice
“The Best All-Rounder: Aircall ... widely considered the gold standard for mid-sized companies” Qwen 3.7 Flash · paraphrase prompt · first choice
“Aircall: Best for cloud-based outbound calling and suitable for mid-market companies.” Llama 4 Maverick · paraphrase 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.