Radar vs Braze
One of fourteen models named Radar first on the direct prompt; one named Braze. Radar was named by eleven of the fourteen models and Braze by seven and Radar carries 29 labels and Braze 18, so the shares are not directly comparable.
New York City, United States, founded 2016. Named in two categories this edition.
New York City, United States, founded 2011. Named in eleven 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 retail, proximity and iot marketing page.
By framing
RadarFirst choices, of fourteen modelsBraze
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 | | |
Radar Braze first choice named as an alternative argued againstblank: not namedEach cell is one answer, Radar on the left and Braze on the right.The direct prompt
Radar first, Braze not the choice
1 of 14 modelsBraze was named in the answer but not as the choice, or not at all.Braze first, Radar not the choice
1 of 14 modelsRadar was named in the answer but not as the choice, or not at all.Neither was the first choice, one was named
3 of 14 modelsThe answer put something else first and named one of the two as an alternative.Neither was named
9 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
What the models said about Radar
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Three of four in this category shown.
“Best for: Sensor-fusion geofencing at scale ... Excellent for retailers and venues needing scalable proximity event ingestion and campaign trigger rules” Kimi K2 · comparative prompt · first choice
“I'd usually recommend Radar if you want one platform that can handle location-based triggers, geofencing, and in-store/proximity experiences” GPT-5.4 mini · paraphrase prompt · first choice
“Or Radar — if you already have an app and want precise geofencing, the $0.02/user cost gives you extreme flexibility.” DeepSeek V4 Flash · budget prompt · first choice
What the models said about Braze
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Three of three in this category shown.
“Avoid: Enterprise tools like Braze/CleverTap (great but $100s+/month post-trial)” Grok 4.1 Fast · budget prompt · hard negative
“Braze (Best for Omnichannel Journeys)... Braze is a leading customer engagement platform that integrates native geofencing capabilities.” GLM 4.7 FlashX · comparative prompt · first choice
“Braze — Strong geofencing, excellent omnichannel campaign orchestration, enterprise-grade, large partner ecosystem.” DeepSeek V4 Flash · scale 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.