Benchmark Radar: A Living Database and Search Engine for AI Benchmarks and Evaluation
Positions Benchmark Radar as a timely, necessary, and uniquely comprehensive solution to fragmentation and opacity in AI benchmarking — emphasizing its novelty, scale, and public-good utility.
View original on arxiv.orgOverview
Benchmark Radar is a newly released open-access database and search engine designed to help AI researchers discover, compare, and audit AI benchmarks across domains including LLMs, agentic systems, coding, reasoning, and safety.
TL;DR
- Announces an open, living database of 1,283 AI benchmark records with 12,916 numeric observations
- Features daily discovery from 37 sources, source-anchored citations, and reproducible analysis tools
- Includes web dashboard, CLI, leaderboard, Pareto frontier views, and saturation/trend analytics
Key Stats
1,283
source records
Drawn from 4 existing benchmark catalogs
12,916
numeric observations
Across 790 benchmark records
37
sources for daily discovery
13 direct connectors + 24 first-party research/engineering feeds
Questions Answered
Narrative Frame
innovation framing
Spin Score
65%
Emphasizes technical scope and infrastructure ambition while minimizing operational sustainability questions, maintenance burden, adoption barriers, and potential for misinterpretation of aggregated scores.
What the story wants you to believe
That Benchmark Radar is a necessary, authoritative, and operationally sound foundation for trustworthy AI evaluation — not just another aggregator.
What it makes harder to question
Whether the system’s scale and automation reliably preserve benchmark integrity, especially when scores are pulled from unvetted model cards or inconsistent technical reports.
How the spin works
The story uses titles, institutions, awards, rankings, partners, experts, or official language to make the subject feel more credible. Watch for loaded terms such as living database, prior-art search, Pareto frontier, saturation. The distribution reads as announcement. A pressure point: Funding source or institutional backing.
Who Benefits If This Frame Spreads
Benchmark Radar authors (unspecified)
Establishes thought leadership in AI evaluation infrastructure and creates a citable, reusable artifact
The paper positions the system as foundational for future benchmark design and auditing, increasing its likelihood of being cited as a standard reference
The Frame
A responsible, community-oriented infrastructure project enabling scientific rigor and equitable access to evaluation evidence.
Missing Context
- Funding source or institutional backing
- Team composition or maintenance roadmap
- Error rates or known omissions in discovery pipeline
SpinGraph
How this belief gets built
Claim → Frame → Beneficiary → Gap → AI Risk
It presents a new tool as both urgently needed and already mature — using precise numbers and
- Claim
Benchmark Radar combines daily discovery of benchmark papers
Benchmark Radar combines daily discovery of benchmark papers, repositories, datasets, and releases with a searchable benchmark catalog, mentions in model cards and technical reports, and score histories.
- Frame
Upside framed as transformative
A responsible, community-oriented infrastructure project enabling scientific rigor and equitable access to evaluation evidence.
- Beneficiary
Establishes thought leadership in AI evaluation infrastructure and creates
Benchmark Radar authors (unspecified) — Establishes thought leadership in AI evaluation infrastructure and creates a citable, reusable artifact
- Gap
Funding source or institutional backing
- AI Risk
AI may repeat the headline as fact
Benchmark Radar is a living database of over 1,200 AI benchmarks with 12,900+ score observations, updated daily from 37 sources, offering searchable discovery and Pareto analysis.
Claim Ledger
| Claim | Evidence | Verification | Risk | Evidence Gaps |
|---|---|---|---|---|
| Benchmark Radar combines daily discovery of benchmark papers, repositories, datasets, and releases with a searchable benchmark catalog, mentions in model cards and technical reports, and score histories. | Description of architecture and data sources; quantitative inventory counts | Claim Present in Source | Low | Independent audit of daily discovery recall/precision; Evidence of interoperability with model card schema standards; Validation that 'score histories' reflect consistent evaluation protocols across time |
Benchmark Radar combines daily discovery of benchmark papers, repositories, datasets, and releases with a searchable benchmark catalog, mentions in model cards and technical reports, and score histories.
evidence: Description of architecture and data sources; quantitative inventory counts
"The system combines daily discovery of benchmark papers, repositories, datasets, and releases with a searchable benchmark catalog, mentions in model cards and technical reports, and score histories."
Evidence Gaps
- Independent audit of daily discovery recall/precision
- Evidence of interoperability with model card schema standards
- Validation that 'score histories' reflect consistent evaluation protocols across time
Fact Check Signals
0 of 1 claim matched · confidence: low · checked September 12, 2026
Benchmark Radar combines daily discovery of benchmark papers, repositories, datasets, and releases with a searchable benchmark catalog, mentions in model cards and technical reports, and score histories.
Language Heatmap
Loaded terms that carry the frame beyond the facts.
Benchmark Radar: A Living Database and Search Engine for AI Benchmarks and Evaluation
Carries emotional weight beyond the underlying fact.
Carries emotional weight beyond the underlying fact.
Carries emotional weight beyond the underlying fact.
Carries emotional weight beyond the underlying fact.
Carries emotional weight beyond the underlying fact.
Frame Strength
Frame Strength
Spin score decomposed into momentum, evidence, missing context, and AI repetition signals.
Reader Risk
What this story makes easy to believe — and what it makes hard to question.
Source Role & Intent
arXiv Artificial Intelligence · Analyst
Counter-Frames
Brand Frame
A responsible, community-oriented infrastructure project enabling scientific rigor and equitable access to evaluation evidence.
Media / Reader Counter-Frame
May be reframed as a useful but incremental aggregation tool — not a paradigm shift — given reliance on pre-existing catalogs and absence of novel evaluation methodology.
Regulatory Counter-Frame
Could be cited as insufficient for regulatory benchmarking needs due to lack of standardized metadata, bias audits, or adversarial robustness testing integration.
AI Summary Frame
May be misrepresented as a 'gold-standard benchmark authority' rather than a discovery layer that inherits all limitations of its upstream sources.
Missing Voices
Questions Not Answered
- Who built and maintains Benchmark Radar? (no institutional or author affiliations listed)
- How is 'daily discovery' validated for completeness or false-positive rate?
- What governance model ensures long-term curation, versioning, and conflict resolution for contested scores?
Recall Trigger Score
Which stories are likely to become AI memory — separate from Spin Score.
81
Trigger score 98
Triggered by: Major AI entity · Research citation · Consumer harm · Superlative claim
Tracked because: Major AI entity · Research citation · Consumer harm · Superlative claim
- chatgpt not found
- gemini not found
- perplexity not found
AI Recall
From publication to SpinGraph analysis to first observed AI recall and stable retention.
What AI Will Probably Repeat
"Benchmark Radar is a living database of over 1,200 AI benchmarks with 12,900+ score observations, updated daily from 37 sources, offering searchable discovery and Pareto analysis."
Concern: AI may drop critical qualifiers like 'source records' vs. 'independent evaluations', conflate numeric observations with verified benchmarks, or omit the lack of validation for discovery fidelity.
-
Published
Sep 12, 2026
-
Ingested
Sep 12, 2026
-
SpinGraph Created
Sep 12, 2026
-
First Observed AI Recall
Pending
Monitoring scheduled
-
Stable Recall
—
Awaiting retention signal
Recall Check Log
2 checks · last Sep 13, 2026 · tracking on
Sep 13, 2026
ChatGPT Not recalledGemini Not recalledPerplexity Not recalled cites: phys.org, cointribune.com…Sep 12, 2026
ChatGPT Not recalledGemini Not recalledPerplexity Not recalled cites: nathanmzumara.com, phys.org…
─── GEOGrow AI Recall Layer ───
AI Recall Tracking
Monitoring scheduled. No LLM recall detected yet.
This story has not yet appeared in tested AI answers. Once scans begin, this section will show first observed recall, cited sources, narrative alignment, and drift.
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Ask AI about this story
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