Sourced AI Benchmarks • Last checked Oct 15, 2026

RankLLMs Research Author

Meet Lucky Yaduvanshi, the founder and editor responsible for RankLLMs model research and editorial analysis.

Portrait of Lucky Yaduvanshi

Founder & Editor

Lucky Yaduvanshi

40 articles published • 95 models tracked • one named editor accountable for published analysis

Software engineer and AI performance researcher focusing on LLM latency, cost efficiency, SWE-bench coding benchmarks, and autonomous agent evaluation.

Why one author

RankLLMs is currently an independent publication with one named founder and editor. That makes ownership and responsibility easy to identify; it does not mean every benchmark is run in-house. We distinguish sourced results from hands-on testing and explain corrections in the editorial policy.

The work is supported by a published scoring methodology, a traceable model directory, and an interactive leaderboard. The methodology also explains where automation is used and which limitations remain.

Editorial standards

Source-aware data
Scorecards separate sourced benchmark results from product specifications; the methodology explains their sources and update path.
Named sources
Benchmark and product information is attributed to the provider or evaluator where available.
Disclosed costs
Where RankLLMs estimates task cost, the calculation states its workload assumptions.
Independence
Vendors cannot buy scores or placement; advertising and affiliate relationships are disclosed.
Public corrections
Verified material corrections are dated on the affected page; report source-backed errors through the contact page.
Testing disclosure
First-party tests are distinguished from external benchmark results and vendor claims.

Most recent publication: Claude Code vs Gemini CLI vs GitHub Copilot CLI (2026 Tested). To suggest a correction or comparison, contact the editor.