Four of fourteen models named ConfigCat first on the direct prompt; three named Statsig. ConfigCat was named by twelve of the fourteen models and Statsig by fourteen and ConfigCat carries 39 labels and Statsig 47, 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 feature flags page.
Across every category in the October 2026 Edition, ConfigCat and Statsig were named in the same answer seventy-one times, of the 116 answers naming ConfigCat and the 131 naming Statsig. In those answers Statsig took the first choice eight times and ConfigCat twenty-eight.
| 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 |
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.
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Six of seven in this category shown.
“It is noted as not a broad experimentation platform. Teams wanting measurement not only toggles tend to look elsewhere.” Muse Glimmer 30B · negative prompt · soft negative
“ConfigCat's hosted model may still be a risk for some regulated industries that require on-premises deployment” GPT-5.4 mini · negative prompt · soft negative
“ConfigCat has no built-in analytics” Claude Haiku 4.5 · negative prompt · soft negative
“I'd usually recommend ConfigCat if your main goal is reliable feature flags with lower complexity and predictable cost” GPT-5.4 mini · paraphrase prompt · first choice
“ConfigCat ⭐ Best for Mid-Market ... Start with ConfigCat if you want simple feature flags with predictable costs” Kimi K2 · direct prompt · first choice
“If I had to choose one for a budget-conscious company that still wants a polished product, I'd choose ConfigCat.” GPT-5.4 mini · budget prompt · first choice
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Six of eight in this category shown.
“if you want a pure-play infrastructure flag tool, look elsewhere, as Statsig has pivoted heavily into Amplitude's analytics-first roadmap” Gemini 3.5 Flash · direct prompt · soft negative
“Statsig is still growing in enterprise governance, with RBAC and audit features that aren't as strong” Claude Haiku 4.5 · negative prompt · soft negative
“Free flags at any scale, but analytics-based pricing can add up” DeepSeek V4 Flash · scale prompt · soft negative
“If you want zero cost + zero maintenance: Go with Statsig. It's the only platform offering truly unlimited feature flags on a free tier” Kimi K2 · budget prompt · first choice
“Widely considered the best all-rounder for startups and mid-size teams in recent years” DeepSeek V4 Flash · comparative prompt · first choice
“LaunchDarkly (if budget allows) or Statsig (if experimentation is a priority)” MiniMax M2.5 · direct 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.