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Herman Miller vs Steelcase

Office chairs60 scenarios

Panel, equal weight

  • Claude Haiku 5.5anthropic/claude-haiku-5.5
  • DeepSeek V4.1 Flashdeepseek/deepseek-v4.1-flash
  • Gemini 3.8 Flashgoogle/gemini-3.8-flash
  • GLM-5.3 Flashz-ai/glm-5.3-flash
  • GPT-6 Lunaopenai/gpt-6-luna
  • Grok 4.7x-ai/grok-4.7
  • Kimi K3.1 Promoonshotai/kimi-k3.1-pro
  • Llama 4 Maverickmeta-llama/llama-4-maverick-17b-128e-instruct
  • Mistral Small 2603mistralai/mistral-small-2603

The answer

LikelyFast panel

Herman Miller

Herman Miller 56.6% · Steelcase 43.4% — all 9 models combined

2 clearly prefer Herman Miller · 6 with no clear preference · 1 clearly prefers Steelcase · excluded: 1 · all 9 counted models are in the overall result

95% interval for Herman Miller: 50.6–62.6%

Detailseach model, intervals, conditions

All models combined

Fast panel

LikelyAll 9 models combined lean Herman Miller (the interval excludes 50%); on their own: 2 clearly prefer Herman Miller · 6 with no clear preference · 1 clearly prefers Steelcase.

Herman Miller56.6%

Steelcase43.4%

  • Confidence interval for Herman Miller: 50.6–62.6%

Consensus95% interval 50.6–62.6%

Each model

Share for the brand named in each row, with its interval

Bar: Herman Miller from the left, Steelcase from the right; dashed line = 50%.

Conditional pick share by judge for the brand named in each row (among scenarios where the judge picked a brand), with confidence intervals. 95% confidence intervals (hull of the scenario-clustered bootstrap and Wilson intervals, widened for small samples in battles and newer boards)
Judge (API model)Brand and shareConfidence intervalLeaningInterval chart
Claude Haiku 5.5Herman Miller: 76%68–83%Clear preference
DeepSeek V4.1 FlashHerman Miller: 49%39–58%No clear preference
Gemini 3.8 FlashHerman Miller: 58%45–70%No clear preference
GLM-5.3 FlashHerman Miller: 51%41–61%No clear preference
GPT-6 LunaHerman Miller: 51%44–58%No clear preference
Grok 4.7Herman Miller: 51%39–63%No clear preference
Kimi K3.1 ProHerman Miller: 57%46–67%No clear preference
Llama 4 MaverickHerman Miller: 90%82–96%Clear preference
Mistral Small 2603Steelcase: 72%64–80%Clear preference

What would you pick?

How votes are counted

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Visitors who voted

Open online poll of Pickbench visitors, not a representative survey.

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How votes are counted

Replay it as a dropSimulated
Herman Miller
Steelcase

Simulation: scenario paths made up to reproduce the published per-judge shares, not measured rows.

The AI consensus leans to Herman Miller

Published 95% confidence interval for Herman Miller: 50.6–62.6%. Press Drop to watch simulated scenarios land.

How to read it

Each ball is a simulated buying scenario. Each row of pins is an AI model, pushing the ball toward the brand it picked.

One drop is one sample. Drop again and the pile shifts; the orange band shows where the balance lands in 95% of drops.

A leader is named only when the band clears the middle. The paths are simulated from the published per-judge shares: no model saw these scenarios.

Tap to drop. Hold to keep dropping.

The numbers behind the machine
Signed snapshot5669ccf2e433JSON
Embed

Free to embed. It shows the latest edition; keep the source line and the link.

Static card (SVG)

How this was measured · verify

How to read

The share is how often the models chose each brand, with its 95% interval. A brand leads only when its whole interval is above 50%, for all models combined and for each model on its own; otherwise it is too close to call.

Each page shows the latest edition. Dates are in the downloadable JSON.

Who was counted

  • The pre-registered inclusion rule counted 9 of the 10 judges on the panel.
  • The results use 60 of the 60 planned scenarios.
Consensus weights of 9 counted judges
Weight of each counted judge in the consensus
Judge (API model)Model familyWeight in the consensus
Claude Haiku 5.5Anthropic11.1%
DeepSeek V4.1 FlashDeepSeek11.1%
Gemini 3.8 FlashGoogle11.1%
GLM-5.3 FlashZ.ai11.1%
GPT-6 LunaOpenAI11.1%
Grok 4.7xAI11.1%
Kimi K3.1 ProMoonshot AI11.1%
Llama 4 MaverickMeta11.1%
Mistral Small 2603Mistral AI11.1%

Judges not counted

jdg-live-qwen3-8-flash-or-v1
Too few valid answers (below the pre-registered minimum) and Answered too few of the planned scenarios

Need-level results

Need-level results are not published: 6 scenarios per need, below the pre-registered minimum of 30.

10 buyer needs
  • Value and easy assembly
  • All-day lower back support
  • Breathable seat for warm rooms
  • Compact home office
  • Heavy-duty frame for years
  • Adjustable armrests
  • Fit for petite and tall people
  • Quiet casters and stable swivel
  • Recline for relaxed reading
  • Stylish for home and camera

Methodology

Each judge is an AI model called through an API; “About this result” names each model and how it was called. In each buyer scenario, the judge chooses between the two brands. The scenario is the unit of analysis.

Version
ACM-1.0
Precision
Measured
Consensus, needs and languages
95% confidence intervals (MOVER combination of the per-judge intervals, widened for small samples in battles and newer boards). The consensus gives equal weight to each model family. The per-judge results in “Each model” are the primary measure.
Per judge
95% confidence intervals (hull of the scenario-clustered bootstrap and Wilson intervals, widened for small samples in battles and newer boards). A single model's view is one judge, not the consensus.
Panel
Fast panel: the fast or small current models of each vendor, not the full flagship panel.

Data warnings

  • Brand names only: the models saw each option as a brand name, with no product facts, and answered from their own knowledge.

About this result

AI models (API)
  • Claude Haiku 5.5
  • DeepSeek V4.1 Flash
  • Gemini 3.8 Flash
  • GLM-5.3 Flash
  • GPT-6 Luna
  • Grok 4.7
  • Kimi K3.1 Pro
  • Llama 4 Maverick
  • Mistral Small 2603

Every model was called via OpenRouter (pinned providers).

Conditions
Each model chose between the two brands in 60 buyer scenarios. Scenario languages: English.
Pre-registration (SHA-256)
747139cc9f57… What the pre-registration fixes
Signed snapshot

Verify this result: download the signed snapshot (JSON)

Signing key (kid)
FnG9tqyrr6Y0… · Production key
SHA-256 of the payload
5669ccf2e433…

How to verify a snapshot

Rank, inclusion and influence on results are never sold.