The best LLM is..... (2nd Qtr 2025 latest ranking)

Video Description

In this video, Tony DeSimone evaluates the top large language models for Q2 2025 using a detailed benchmark system across 18 categories. From pricing and privacy to mobile features and creative capabilities, Tony breaks down what practical users need to know before choosing an LLM. Link to LLM ranking sheet - https://drive.google.com/file/d/1U8aQH-U4Y4n5JYFhLH0Jx7obVB8ln75m/view?usp=sharing 📊 Timeline Summary: 00:03 – Quarterly Rankings Return: A new set of rankings for Q2 begins, continuing from Q1’s results. 00:28 – Evaluation Scope: Focus is strictly on large language models (LLMs), not specialized tools. 00:40 – Models Included: Leading LLMs from OpenAI, Microsoft, Google, Anthropic, Meta, Perplexity, and X. 01:06 – Free Access Comparison: All models offer some version for users to try before buying. 01:25 – Peer Preference Benchmark: LLMs were asked which competitor they'd choose if not themselves. 01:58 – Pricing Benchmark: A breakdown of the most affordable paid options, including open-source models. 02:29 – Knowledge Base Freshness: Assessment of each model's training data recency. 02:55 – Mobile App Availability: Whether the model has a functioning mobile experience. 03:10 – Voice-to-Voice Interaction: Which tools support real-time conversation on desktop and mobile. 03:50 – Visual Analysis Tools: Identifies which LLMs offer real-time image interaction. 04:20 – Input Privacy Options: Which models allow users to opt out of training on their data. 04:39 – Multilingual Support: All models translate 100+ languages, sharing points. 04:51 – Security & Compliance: All offer encryption comparable to major cloud platforms. 05:24 – Creativity Benchmark: LLMs rank each other on creativity in output. 06:07 – Image Generation Quality: Review of each model’s visual output capabilities. 06:20 – Search Accuracy: Which LLMs are most effective for real-time, web-connected search. 06:34 – Coding & Development Use: Ranking for best performance in writing and debugging code. 06:48 – Document Writing: Which model excels in producing structured, long-form content. 07:24 – Hallucination Reality Check: All models hallucinate—users must still verify responses. 08:03 – Deep Research Functionality: A newer benchmark focused on depth and thoroughness in complex queries. 08:50 – API Availability: All tested models provide API access, points shared. 09:08 – Final Ranking Results: Full scores calculated—some models climb, others fall. 10:00 – Trends & Forecasts: One model is rising quickly, another may start slipping. 10:42 – Funding & Momentum: Financial backing and valuations are influencing future development. 11:46 – Tony’s Personal Stack: Shares how he uses each model day-to-day and how preferences are shifting. 13:37 – Closing Thoughts: Expect more movement next quarter as features evolve and competition intensifies.