What AI recommends for authentication
When developers ask “What should I use for auth?”, this is what Claude · Claude Haiku 4.5, Claude · Claude Opus 4.8, Claude · Claude Sonnet 4.6, ChatGPT, Gemini, Venice · DeepSeek V4 Flash 0731, Venice · Gemini 3.6 Flash, Venice · Kimi K2.6, Venice · Llama 3.3 70B, Venice · Qwen 3.7 Plus and Venice · GLM 5.2 answer. Few categories swing as hard as auth: pricing changes and migration stories move developer opinion fast, while AI answers update on their own schedule. This board shows which auth providers the models recommend and whether the developers who use them agree.
Standings frozen August 2026 · methodology · View as Markdown
AI share of voice · August 2026
839 sampled answers · 11 models
- 1Auth0new28%Claude Haiku 4.5 · Claude Opus 4.8 · Claude Sonnet 4.6 · GPT · Gem · DeepSeek V4 Flash 0731 · Kimi K2.6 · Llama 3.3 70B · GLM 5.2· quiet
- 2Clerknew22.6%Claude Haiku 4.5 · Claude Opus 4.8 · Claude Sonnet 4.6 · GPT · Gem · DeepSeek V4 Flash 0731 · Kimi K2.6 · GLM 5.2—
- 3Supabase Authnew20.9%Claude Haiku 4.5 · Claude Opus 4.8 · Claude Sonnet 4.6 · GPT · Gem · DeepSeek V4 Flash 0731 · Kimi K2.6 · Llama 3.3 70B · GLM 5.2· quiet
- 4Keycloaknew17.1%Claude Haiku 4.5 · Claude Opus 4.8 · Claude Sonnet 4.6 · GPT · Gem · DeepSeek V4 Flash 0731 · Kimi K2.6 · Llama 3.3 70B · GLM 5.2—
- 5WorkOSnew11.2%Claude Haiku 4.5 · Claude Opus 4.8 · Claude Sonnet 4.6 · GPT · DeepSeek V4 Flash 0731 · Llama 3.3 70B · GLM 5.2—
- 6Firebase Authnew10.9%Claude Haiku 4.5 · Claude Opus 4.8 · Claude Sonnet 4.6 · GPT · DeepSeek V4 Flash 0731 · Llama 3.3 70B · GLM 5.2—
Share of voice weights each compared model equally: it is the average, across the models, of how often each one named the tool in its own answers, so a model probed more than another can't skew it. Model chips list which AI models named it this month; the pulse is the sentiment of that month's developer mentions across Hacker News, Reddit, GitHub, Stack Overflow, Bluesky and more.
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Averaged equally across 11 AI models, Auth0 is named in 28% of answers about authentication (9 of 11 name it).
The 3 prompts behind these standings
- ›What should I use for auth? (recommendation)
- ›What are the best Auth0 alternatives? (alternatives)
- ›Which authentication provider is best for a startup? (recommendation)
Each prompt is sampled several times per model per probe because answers vary run to run; 839 answers across 11 probe runs fed this month.
Frequently asked questions
How is the authentication ranking computed?
BackTalk asks Claude, ChatGPT, Gemini and Perplexity a fixed set of buyer questions about authentication, several samples per prompt because answers vary run to run, then extracts which tools each answer recommends. A tool's share of voice is the percentage of all sampled answers that name it. The prompts, sample counts, and models are published on every page; the raw method is the same probe engine BackTalk customers run on their own brands.
How often do the standings update?
Monthly. The current month is a live preview that updates as new answers come in; once the month ends its standings are finalized and never change after that, so a cited number stays exactly what it was when you cited it. Past months keep their own permalink in the archive, and month-over-month deltas track who is rising and falling.
What does the developer pulse column mean?
BackTalk also listens where developers actually talk: Hacker News, Reddit, GitHub, Stack Overflow, Bluesky and more. The pulse column summarises the sentiment of that month's developer mentions for each ranked tool, which is how the board can show AI recommending a tool developers are souring on, or overlooking one they praise.
Is AI recommending your tool?
BackTalk runs these same probes for any product: your prompts, your competitors, your share of voice on your own keys, next to every public developer mention of your brand.
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