About RankLLMs
Learn about RankLLMs, founded by Lucky Yaduvanshi. We deliver transparent, data-driven AI model comparisons, LLM benchmarks, and CLI coding agent reviews.
Our Mission: Transparent, Independent AI Benchmarks
At RankLLMs, our core objective is to provide developers, AI researchers, software engineers, and enterprise leaders with transparent, reproducible, and vendor-neutral Large Language Model evaluations. In an ecosystem saturated with marketing claims, RankLLMs cuts through the noise with real-world software engineering data.
What We Benchmark & Evaluate
We conduct standardized evaluations comparing proprietary frontier engines (GPT-5.6 Sol, Claude Opus 5, Claude Fable 5, Gemini 3.7 Flash, Grok 4.6) and open-weights architectures (Kimi K3, GLM-5.3, DeepSeek-V4 Pro, Qwen3.8 Max, Muse Spark 1.1) across six key pillars:
- SWE-bench Coding Accuracy
Testing repository refactoring, lint error remediation, and bug fixing ability.
- Formal Logic & Math
MATH-500, GPQA Diamond, and symbolic reasoning performance evaluation.
- TTFT Latency & Generation Speed
Real-world streaming latency measurements and tokens per second throughput.
- API Cost Efficiency
Comparing input/output token pricing per 1M tokens to optimize developer API budgets.
- Terminal CLI Agent Reviews
Field-testing tools like Claude Code, Freebuff AI, Gemini CLI, and Copilot CLI.
- Free AI Credits & Grants
Weekly tracking of verified API starter credits, promo codes, and free tier quotas.
How We Work
Every ranking and article on RankLLMs is built from verifiable signals: official model cards and vendor pricing pages, independent benchmark organizations, and our own documented test runs. Every scorecard shows when its data was last verified, historical results are labeled with the exact model version they belong to, and our methodology page explains the composite scoring formula, sources, and update cadence in full.
Our editorial policy covers sourcing rules, corrections, and how AI tools are (and are not) used in production. Short version: claims trace to named sources, errors are corrected publicly, and no vendor can buy a position or a review outcome.
Independence & Funding
RankLLMs is an independent publication, not owned by or affiliated with any AI provider. Rankings are never sold: labs cannot preview, influence, or purchase placement on the leaderboard, in the benchmark guides, or in any review. The site is funded by its founder, and when advertising or affiliate relationships are introduced, they will be disclosed on the pages where they appear and will never affect scores or verdicts.
Found a bug in our data, or represent a lab with newer official results? We verify and correct in public - reach us through the contact page.
Founded by Lucky Yaduvanshi
RankLLMs was created by Lucky Yaduvanshi, a Software Engineer, DevOps Specialist, and AI Researcher. With a passion for performance optimization, Lucky built RankLLMs to give the global developer community clear, unbiased data on artificial intelligence capabilities.