8x8 vs Dialpad
One of fourteen models named 8x8 first on the direct prompt; one named Dialpad. 8x8 was named by thirteen of the fourteen models and Dialpad by thirteen and 8x8 carries 37 labels and Dialpad 31, so the shares are not directly comparable.
Named in two categories this edition.
Named in two categories 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 business phone systems page.
By framing
8x8First choices, of fourteen modelsDialpad
Across every category in the October 2026 Edition, 8x8 and Dialpad were named in the same answer thirty-one times, of the 88 answers naming 8x8 and the 88 naming Dialpad. In those answers Dialpad took the first choice zero times and 8x8 two.
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 | | |
8x8 Dialpad first choice named as an alternative argued againstblank: not namedEach cell is one answer, 8x8 on the left and Dialpad on the right.The direct prompt
8x8 first, Dialpad an alternative
1 of 14 modelsDialpad was named in the answer but not as the choice, or not at all.Dialpad first, 8x8 not the choice
1 of 14 models8x8 was named in the answer but not as the choice, or not at all.Neither was the first choice, one was named
8 of 14 modelsThe answer put something else first and named one of the two as an alternative.Neither was named
4 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
8x83%#6 of 12Dialpad2%#8 of 12What the models said about 8x8
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Six of seven in this category shown.
“While 8x8 has strengths, it has significant red flags... budget-conscious growing teams may find pricing unpredictable.” Qwen 3.7 Flash · negative prompt · soft negative
“notorious for aggressive and highly restrictive sales contracts” Gemini 3.5 Flash · negative prompt · soft negative
“Support is consistently rated 1–2 stars on third-party sites.” DeepSeek V4 Flash · negative prompt · soft negative
“RingCentral MVP / 8x8 X Series: Full UCaaS, strong PBX features, good mid-market fit.” Kimi K2 · scale prompt · first choice
“I'd suggest RingCentral RingEX or 8x8 as the top choices” Kimi K2 · direct prompt · first choice
“If you're running both sales and support operations, 8x8 is worth a serious look given its native contact center capabilities.” DeepSeek V4 Flash · paraphrase prompt · alternative
What the models said about Dialpad
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Four of five in this category shown.
“Trustpilot highlights awful customer service, refund delays, hidden fees (e.g., porting charges), and app glitches.” Grok 4.1 Fast · negative prompt · soft negative
“and Dialpad (to see how live AI transcription can boost your sales reps' close rates)” Gemini 3.5 Flash · direct prompt · first choice
“Dialpad leads with AI transcription and coaching” GLM 4.7 FlashX · comparative prompt · first choice
“If AI call intelligence is the primary driver, Dialpad has the most mature AI coaching and transcription stack at a mid-market price” Muse Glimmer 30B · direct prompt · alternative
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.