AudioGo vs Triton Digital
Two of fourteen models named AudioGo first on the direct prompt; one named Triton Digital. AudioGo was named by thirteen of the fourteen models and Triton Digital by ten and AudioGo carries 37 labels and Triton Digital 13, 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 audio and podcast advertising page.
By framing
AudioGoFirst choices, of fourteen modelsTriton Digital
Across every category in the October 2026 Edition, AudioGo and Triton Digital were named in the same answer eighteen times, of the 112 answers naming AudioGo and the 43 naming Triton Digital. In those answers Triton Digital took the first choice two times and AudioGo seven.
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 | | | |
AudioGo Triton Digital first choice named as an alternative argued againstblank: not namedEach cell is one answer, AudioGo on the left and Triton Digital on the right.The direct prompt
AudioGo first, Triton Digital not the choice
2 of 14 modelsTriton Digital was named in the answer but not as the choice, or not at all.Triton Digital first, AudioGo an alternative
1 of 14 modelsAudioGo was named in the answer but not as the choice, or not at all.Neither was the first choice, one was named
1 of 14 modelsThe answer put something else first and named one of the two as an alternative.Neither was named
10 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
AudioGo49%#1 of 10Triton Digital2%#– of 10AudioGo34%#1 of 11Triton Digital2%#6 of 11AudioGo6%#5 of 14Triton Digital2%#10 of 14What the models said about AudioGo
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Four of five in this category shown.
“a $250 campaign is more of a test and not scalable... only supports pre-produced audio” Mistral Small · negative prompt · soft negative
“AudioGo is the safest recommendation from the search results because it combines a low entry point with broad access and simple self-serve setup” Perplexity Sonar · budget prompt · first choice
“All-in-One Audio Network | AudioGO, Triton, AdsWizz | You want to cast a wide net across hundreds of smaller podcasts” Qwen 3.7 Flash · scale prompt · first choice
“I'd suggest starting with Acast or AudioGo — both offer low entry points ($250), self-serve flexibility, and strong targeting” Kimi K2 · direct prompt · first choice
What the models said about Triton Digital
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Three of four in this category shown.
“1. Triton Digital: Offers 100B+ monthly impressions with native integration with The Trade Desk.” Llama 4 Maverick · direct prompt · first choice
“Best for Programmatic/Premium Inventory ... Best when you want to buy premium audio inventory at scale” MiniMax M2.5 · paraphrase prompt · alternative
“fits buyers and publishers wanting to plug into a broad audio exchange with established measurement” Claude Haiku 4.5 · comparative 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.