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Payments: August 2026

The final August 2026 standings for “What should I use to accept payments?”. These numbers are fixed and can be cited by permalink. See the current standings.

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AI share of voice · August 2026

935 sampled answers · 11 models

  1. 1Stripenew34.2%
    Claude Haiku 4.5 · Claude Opus 4.8 · Claude Sonnet 4.6 · GPT · Gem · DeepSeek V4 Flash 0731 · Gemini 3.6 Flash · Kimi K2.6 · Llama 3.3 70B · GLM 5.2
  2. 2PayPalnew28.5%
    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
  3. 3Squarenew24.3%
    Claude Haiku 4.5 · Claude Opus 4.8 · Claude Sonnet 4.6 · GPT · DeepSeek V4 Flash 0731 · Kimi K2.6 · Llama 3.3 70B · GLM 5.2
  4. 4Paddlenew21.6%
    Claude Haiku 4.5 · Claude Opus 4.8 · Claude Sonnet 4.6 · GPT · Gem · DeepSeek V4 Flash 0731 · Gemini 3.6 Flash · Kimi K2.6 · Llama 3.3 70B · GLM 5.2
  5. 5Adyennew18.9%
    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
  6. 6Lemon Squeezynew13.8%
    Claude Haiku 4.5 · Claude Opus 4.8 · Claude Sonnet 4.6 · GPT · Gem · DeepSeek V4 Flash 0731 · Gemini 3.6 Flash · Kimi K2.6 · 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, Stripe is named in 34.2% of answers about payments (10 of 11 name it).
Source: BackTalk AI Recommendation Standings, August 2026 · backtalk.sh/ai-recommends/payments/2026-08
The 3 prompts behind these standings
  • What should I use to accept payments? (recommendation)
  • What are the best Stripe alternatives? (alternatives)
  • Which payment provider is best for a SaaS? (recommendation)

Each prompt is sampled several times per model per probe because answers vary run to run; 935 answers across 12 probe runs fed this month.