Deepchecks LLM Evaluation
Validate, monitor, and safeguard LLM-based apps
Deepchecks LLM Evaluation launched on November 28, 2023 with 205 votes, #210 of 4,333 launches that month and more than 95% of that year's launches. The site was still online in September 2026, 2 years on.
What it does
Continuously validate LLM-based applications including LLM hallucinations, performance metrics, and potential pitfalls throughout the entire lifecycle from pre-deployment and internal experimentation to production.🚀
Comprehensive guide to evaluating LLMs. Metrics, fairness, safety, deployment best practices & frameworks
Large Language Models (LLMs) have emerged as pivotal technologies in the rapidly evolving landscape of artificial intelligence, revolutionizing how we interact with digital systems-captivating the imagination of researchers, developers, businesses, and society. From automating customer service to enhancing natural language understanding and generating human-like text, the applications of LLMs span an increasingly broad and diverse range of fields. This exponential growth in LLM applications underscores a burgeoning interest in these technologies, not only for their potential to streamline and enhance various processes but also for their ability to drive innovation in areas previously…from deepchecks.com
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LLM StatsOct 2025 · llm-stats.com · ▲293I was overspending on GPT-4o. It was really hard to compare different models I could switch to, so I built this LLM comparison tool. It shows leaderboards, pricing, and performance data across 100+ LLMs (including all major providers and open-source models). Key features: - Live pricing comparisons - Benchmark Scores (MMLU, HumanEval, GPQA, etc.) - Context length vs cost analysis - Speed/throughput tests across providers - Quality vs price visualizations - Open source (all data verifiable) Try it out: https://llmstats.com I'd like to know your opinion :) Tech stack: Next.js,…


I implemented evals metrics for LLMs that runs locally on your machine2023 · github.com · ▲22The LLM Evaluation Framework. Contribute to confident-ai/deepeval development by creating an account on GitHub.
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