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профилактика религиозного экстремизма в школе отчет, LLM Leaderboard 2025 - Verified AI Rankings, Best 44 Large Language Models (LLMs) in 2025 - Exploding Topics, 15 Best LLM Models in 2025 | Top AI Language Models Ranked, 10 Best Large Language Models (LLMs) in 2025 - Beebom, Best LLM Models 2025: Top 10 AI Models Ranked & Compared, 10 Best Large Language Models (LLMs) in 2025 - ZEGOCLOUD, Top 9 Large Language Models as of June 2025 - Shakudo.
LLM Leaderboard 2025 - Verified AI Rankingsllm-stats.comLeaderboardComparisonsToggle themeIssues? / Missing data?Contribute on GitHub LLM LeaderboardAnalyze and compare AI models across benchmarks, pricing, and capabilities. Live Benchmarks Updated daily Tracking official benchmarks & pricing data from leading organizationsLoading timeline...LLM RankingsBest models and API providers in each categoryBenchmarksLeaderboards about code, reasoning and general knowledgeContext WindowMaximum input context length for each modelWhile tokenization varies between models, on average, 1 token ≈ 3.5 characters in English.Note: Each model uses its own tokenizer, so actual token counts may vary significantly.As a rough guide, 1 million tokens is approximately equivalent to:30 hoursof a podcast~150 words per minute1,000 pagesof a book~500 words per page60,000 lines1of code~60 characters per line[1] Based on average characters per line. See .ComparisonsLLM comparisons across benchmark scores, prices, and model sizesAPI Providers - Open LLM ProvidersPrice and performance across providers for Llama 4 MaverickProvider performance varies significantly. Some providers run full-precision models on specialized hardware accelerators (like Groq's LPU or Cerebras' CS-3), while others may use quantization (4-bit, 8-bit) to simulate faster speeds on commodity hardware. Check provider documentation for specific hardware and quantization details, as this can impact both speed and model quality.QualityFP16/BF168-bit/4-bitSpeedModel Quantization Trade-offQualityFP16/BF16Model Quantization Trade-off8-bit/4-bitSpeedObserve how different processing speeds affect real-time token generation.Try adjusting the speeds using the number inputs above each panel ↑t/st/st/sValues reset every 5 seconds to demonstrate different speedsPopular LLM ComparisonsModel ComparisonClaude 3.7 SonnetvsClaude 3.5 SonnetModel ComparisonClaude 3.7 Sonnetvso1Model ComparisonClaude 3.7 SonnetvsGrok 3Model ComparisonClaude 3.7 Sonnetvso3-miniModel ComparisonGrok 3vso1Model ComparisonDeepSeek R1vso1LLM Stats © 2025 • Follow us If this website has been helpful, please consider citing it in your work., Explore the leaderboard and compare AI models by context window, speed, and price. Access benchmarks for LLMs like GPT-4o, Llama, o1, Gemini, and Claude., As adoption continues to grow, so does the LLM industry. Here's a deeper dive on some of the most important models over the last 3 years. 1. GPT-4.5. Developer: OpenAI. Release date: February 2025. Number of Parameters: Unknown. Context Window (Tokens): 128,000. Knowledge Cutoff Date: October 2023. What is it?.
Explore the 15 best LLM models in 2025, including GPT-4, Gemini, LLaMA, and more. Compare performance, capabilities, and find out what are the best LLM models for your use case., To find out, follow our list of the best large language models (LLMs) in 2025. 1. OpenAI o3 and o1. When ChatGPT was launched in late 2022, OpenAI was the leader with the best large language model with its GPT-3 series models. And even today in 2025, OpenAI reigns supreme with its o-series reasoning models., From early models like GPT-3 to the latest top LLM models of 2025, AI has become smarter, faster, and more versatile. Today’s best LLM models provide better accuracy, real-time responses, and advanced reasoning capabilities to make them necessary for AI-powered applications., Discover the best LLM 2025 powering smarter AI. Learn their key use cases and what to expect in the future of large language models., Below, we highlighted the top 9 LLMs that we think are currently making waves in the industry, each with distinct capabilities and specialized strengths, excelling in areas such as natural language processing, code synthesis, few-shot learning, or scalability., In 2025, the focus has shifted: from general-purpose LLMs to models tailored for specific industries and tasks. From simple assistants to autonomous agents that act on our behalf. This article explores what happened in 2024, and what to expect in the future of LLMs. In 2024, LLM developers focused on making models smaller and more efficient..