# Appcast vs Broadbean: which do AI models recommend for job advertising, October 2026

HR AI Recommendation Index, October 2026 Edition, Job advertising and distribution. Three of fourteen models named Appcast first on the direct prompt; zero named Broadbean. Page: https://hr-ai-index.com/talent/job-advertising-and-distribution/appcast-vs-broadbean/

| | First-choice share | Rank | Negative rate | Labels | Models naming it |
|---|---|---|---|---|---|
| Appcast | 15% | #2 of 14 | 15% | 34 | 14 of 14 |
| Broadbean | 2% | #7 of 14 | 9% | 11 | 9 of 14 |

## The direct prompt, model by model

- DeepSeek V4 Flash: appcast first (first choices: Appcast) (alternatives: Joveo, Talroo, VONQ)
- Qwen 3.7 Flash: appcast first (first choices: Appcast) (alternatives: Joveo, LinkedIn Ads, Talroo)
- MiniMax M2.5: appcast first (first choices: Appcast, LinkedIn Talent Solutions) (alternatives: Adway, Indeed Programmatic, PandoLogic)
- Claude Haiku 4.5: neither first, one named (first choices: Joveo) (alternatives: Appcast, JobTarget)
- GPT-5.4 mini: neither first, one named (first choices: Joveo) (alternatives: Appcast, JobTarget, Talroo, Veritone Hire)
- Perplexity Sonar: neither first, one named (first choices: StackAdapt) (alternatives: 6sense, Appcast, Demandbase)
- Grok 4.1 Fast: neither first, one named (first choices: PandoLogic) (alternatives: Appcast, Recruitics)
- Kimi K2: neither first, one named (first choices: Joveo) (alternatives: Appcast)
- GLM 4.7 FlashX: neither first, one named (first choices: JobTarget) (alternatives: Appcast, Joveo, PandoLogic, Recruitics)
- GPT-6 Luna: neither first, one named (first choices: JobTarget Programmatic+) (alternatives: Appcast)
- Muse Glimmer 30B: neither first, one named (first choices: Joveo) (alternatives: Appcast)
- Gemini 3.5 Flash: neither named (first choices: Adway) (alternatives: JobTarget, Joveo, Veritone Hire)
- Mistral Small: neither named (first choices: Adaptive Talent) (alternatives: JobAdX, TalentBurst)
- Llama 4 Maverick: neither named

## What the models said about Appcast

- "Avoid these on a tight budget: These platforms charge monthly software fees ranging from $500 to $2,000+ per month." (Qwen 3.7 Flash, budget prompt, hard negative)
- "While enterprise heavyweights like *Appcast* and *Joveo* are industry giants... ask specifically for their managed services ... so you aren't overwhelmed by enterprise-level complexity." (Gemini 3.5 Flash, scale prompt, soft negative)
- "buying a massive, standalone enterprise distribution tool (like Broadbean or Appcast) is often overkill and highly inefficient" (Gemini 3.5 Flash, paraphrase prompt, soft negative)
- "Choose Appcast if: You are primarily hiring in North America... You want the industry standard with proven reliability." (Qwen 3.7 Flash, direct prompt, first choice)
- "For most mid-market B2B companies, [Appcast](https://www.appcast.com) is the strongest overall choice" (DeepSeek V4 Flash, direct prompt, first choice)
- "Some options to consider include Appcast, which has a minimum campaign spend of $200-$300" (Llama 4 Maverick, budget prompt, first choice)

## What the models said about Broadbean

- "buying a massive, standalone enterprise distribution tool (like Broadbean or Appcast) is often overkill and highly inefficient" (Gemini 3.5 Flash, paraphrase prompt, soft negative)
- "I'd recommend Broadbean if your priority is reliable multi-channel job distribution" (Perplexity Sonar, paraphrase prompt, first choice)
- "Excellent if you want a hybrid of traditional job posting (flat-fee boards) and programmatic performance-based posting in a single interface." (Gemini 3.5 Flash, scale prompt, alternative)
- "Broadbean is a solid alternative when repeatable feed-based multiposting is the priority." (Muse Glimmer 30B, budget prompt, alternative)

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.