BullshitBench v2

BullshitBench measures whether models detect nonsense, call it out clearly, and avoid confidently continuing with invalid assumptions.

• Public viewer (latest): https://petergpt.github.io/bullshit-benchmark/viewer/index.v2.html
• Updated: 2026-05-07

Latest Changelog Entry (2026-05-07)

• Added GPT-5.5 chat benchmark results to both published tracks: v1 with 55 questions and v2 with 100 questions.
• Published:
  • openai/gpt-5.5-chat@reasoning=default
• v1 score: 0.6303 average, 8 Clear Pushback, 20 Partial Challenge, 27 Accepted Nonsense.
• v2 score: 1.0133 average, 34 Clear Pushback, 39 Partial Challenge, 27 Accepted Nonsense.
• Recorded openai/gpt-5.5-chat as the benchmark display row for OpenAI's chat-latest API slug, since the slug does not expose the GPT-5.5 chat-family name directly.
• Updated durable v1/v2 config coverage and refreshed the published leaderboard, release-date, reasoning-token/cost, and model-size chart data from completed 3-judge panels.
• Full details: CHANGELOG.md

v2 Changelog Highlights

• 100 new nonsense questions in the v2 set.
• Domain-specific question coverage across 5 domains: software (40), finance (15), legal (15), medical (15), physics (15).
• New visualizations in the v2 viewer, including:
  • Detection Rate by Model (stacked mix bars)
  • Domain Landscape (overall vs domain detection mix)
  • Detection Rate Over Time
  • Do Newer Models Perform Better?
  • Does Thinking Harder Help? (tokens/cost toggle)
  • Model Size and Weights (total/active parameter scatter views)

Viewer Walkthrough (v2)

The screenshots below follow the same flow as viewer/index.v2.html, starting with the main chart.

1. Detection Rate by Model (Main Chart)

Primary leaderboard-style view showing each model's green/amber/red split.

2. Domain Landscape

Detection mix by domain to compare overall performance vs each domain at a glance.

3. Detection Rate Over Time

Release-date trend view focused on Anthropic, OpenAI, and Google.

4. Do Newer Models Perform Better?

All-model scatter by release date vs. green rate.

5. Does Thinking Harder Help?

Reasoning scatter (tokens/cost toggle in the viewer) vs. green rate.

6. Model Size and Weights

Total and active parameter scatter views for models with public size metadata.

Benchmark Scope (v2)

• 100 nonsense prompts total.
• 5 domain groups: software (40), finance (15), legal (15), medical (15), physics (15).
• 13 nonsense techniques (for example: plausible_nonexistent_framework, misapplied_mechanism, nested_nonsense, specificity_trap).
• 3-judge panel aggregation (anthropic/claude-sonnet-4.6, openai/gpt-5.2, google/gemini-3.1-pro-preview) using full panel mode + mean aggregation.
• Published v2 leaderboard currently includes 156 model/reasoning rows.

What This Measures

• Clear Pushback: the model clearly rejects the broken premise.
• Partial Challenge: the model flags issues but still engages the bad premise.
• Accepted Nonsense: the model treats the nonsense as valid.

Quick Start

1. Set API keys:

export OPENROUTER_API_KEY=your_key_here
export OPENAI_API_KEY=your_openai_key_here  # required only for models routed to OpenAI
export OPENAI_PROJECT=proj_xxx              # optional: force OpenAI requests to a specific project
export OPENAI_ORGANIZATION=org_xxx          # optional: force organization context

Provider routing is configured per model via collect.model_providers and grade.model_providers in config (default is OpenRouter), for example: {"*":"openrouter","gpt-5.3":"openai"}.

2. Run collection + primary judge (Claude by default):

./scripts/run_end_to_end.sh

3. Run v2 end-to-end and publish into the dedicated v2 dataset:

./scripts/run_end_to_end.sh --config config.v2.json --viewer-output-dir data/v2/latest --with-additional-judges

4. Optionally run the default config end-to-end (publishes to data/latest):

./scripts/run_end_to_end.sh --with-additional-judges

5. Open the viewer:

• Published viewer (latest): https://petergpt.github.io/bullshit-benchmark/viewer/index.v2.html
• Local viewer (optional):

./scripts/run_end_to_end.sh --with-additional-judges --serve --port 8877

Then open http://localhost:8877/viewer/index.v2.html. Use the Benchmark Version dropdown in the filters panel to switch between published datasets (for example v1 and v2).

Published Datasets

• v1 dataset remains in data/latest.
• v2 dataset is published in data/v2/latest.
• v2 question set comes from drafts/new-questions.md via scripts/build_questions_v2_from_draft.py.
• Canonical judging is now fixed to exactly 3 judges on every row with mean aggregation (legacy disagreement-tiebreak mode is retired from the main pipeline).
• Release notes and notable changes are tracked in CHANGELOG.md.

Documentation

• Technical Guide: pipeline operations, publishing artifacts, launch-date metadata workflow, repo layout, env vars.
• Changelog: v1 to v2 release notes and publish-history highlights.
• Question Set: benchmark questions and scoring metadata.
• Question Set v2: v2 question pool generated from drafts/new-questions.md.
• Config: default model/pipeline settings.
• Config v2: v2-ready config (uses questions.v2.json).

Notes

• This README is intentionally audience-facing.
• Technical and maintainer-oriented content lives in docs/TECHNICAL.md.

License

MIT. See LICENSE.

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