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Running shoes

Which brand 4 AI models pick, with intervals.

51 scenariosBetaBrand names only

Fast panel · Panel, equal weight

  • anthropic/claude-haiku-5.5 @ claude-haiku-5.5 via OpenRouter (25%)
  • openai/gpt-6-luna @ gpt-6-luna via OpenRouter (25%)
  • google/gemini-4-argon @ gemini-4-argon via OpenRouter (25%)
  • mistralai/mistral-large-4-0 @ mistral-large-4-0 via OpenRouter (25%)

Too closeNo single favourite: Altra, ASICS, Brooks, HOKA, New Balance, and Saucony share the top tier for these 4 API models.

Choice share · 95% interval
0255075100

Tier 1

  1. Brooks55%95% interval 42–68%plausible rank 1–6
  2. Saucony46%95% interval 35–59%plausible rank 1–6
  3. HOKA34%95% interval 22–48%plausible rank 1–9
  4. ASICS33%95% interval 22–46%plausible rank 1–9
  5. New Balance32%95% interval 21–44%plausible rank 1–9
  6. Altra19%95% interval 9–33%plausible rank 1–11

Tier 2

  1. Nike16%95% interval 6–29%plausible rank 3–11
  2. On13%95% interval 6–23%plausible rank 3–11
  3. adidas13%95% interval 6–22%plausible rank 3–11
  4. PUMA7%95% interval 2–14%plausible rank 6–11
  5. Mizuno5%95% interval 2–12%plausible rank 6–11
How to read this
  • Choice share: how often models pick a brand when it appears in a shortlist of 4. Chance is 25%, the dashed line.
  • The band is the 95% interval; the bright tick is the estimate. Overlapping bands are not a strict order.
  • Tiers are published: a tier groups brands not distinguishable from that tier's leader. Same tier does not mean equal.
  • Rank shows the plausible rank range, not a strict place.
  • Drag across the chart to probe a share and see which intervals contain it.
  • Brand names only: the models saw each option as a brand name, with no product facts, and answered from their own knowledge.
  • Fast panel: the fast or small current models of each vendor, not the full flagship panel.
  • Beta: intervals are not yet small-sample calibrated.
  • Each page shows the latest edition. Dates are in the downloadable JSON.

Panel and conditions

Each edition puts the brands of the category to a panel of AI models, called through their APIs, in randomized shortlists of 4 (chance is 25%). Each option was a brand name only, with no product facts, prices or any commercial data, so a brand's share measures which brand the models recommend from their own knowledge for the shopper needs of the scenarios. Shares come with 95% intervals; tiers and rank intervals are simultaneous at the same level.

  • anthropic/claude-haiku-5.5 @ claude-haiku-5.5 via OpenRouter (25%)
  • openai/gpt-6-luna @ gpt-6-luna via OpenRouter (25%)
  • google/gemini-4-argon @ gemini-4-argon via OpenRouter (25%)
  • mistralai/mistral-large-4-0 @ mistral-large-4-0 via OpenRouter (25%)

Conditions: closed-book API calls via OpenRouter (pinned providers); web search, grounding, tools and retrieval off; forced choice; 2 paraphrases per scenario in English.

Methodology: ACM-1.0-chart-draft (draft rules for movement, significance and events, awaiting review).

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