Based on the latest search results (as of July 2025), here is an LLM ranking of the top 15 most popular LLMs, categorized by proprietary and open-source models, sorted by benchmark performance, enterprise adoption, and industry recognition. Each entry includes key specs, strengths, and popularity drivers:
🏆 Top 15 LLM Ranking by Popularity (Mid-2025)
(Ranked by performance + adoption + innovation)
Proprietary Models (Closed API Access)
- Gemini 2.5 Pro (Google DeepMind)
- Key specs: 1M context, multimodal (text/image/video), $2.5/$15 per 1M I/O tokens.
- Strengths: #1 in reasoning (86.4% GPQA Diamond), 92% AIME math, Google Workspace integration.
- Popularity: Leading enterprise adoption; iPhone integration pending.
- Claude 4 Opus (Anthropic)
- Key specs: 200K context, $15/$75 per 1M I/O tokens, 72.5% SWE-bench (coding).
- Strengths: World’s best coding LLM; “Extended Thinking Mode” for step-by-step logic.
- Popularity: Integrated with Apple Xcode; top choice for developers.
- Grok-3 (xAI)
- Key specs: 1M context, real-time web search via X, $3/$15 per 1M tokens.
- Strengths: 93.3% AIME math, 84.6% GPQA; “DeepSearch” for live data.
- Popularity: Critical for finance/news analytics; trained on 200K H100 GPUs.
- OpenAI o3 (OpenAI)
- Key specs: 200K context, $10/$40 per 1M tokens, 83.3% GPQA.
- Strengths: STEM specialist (91.6% AIME); optimized for scientific research.
- GPT-4.5 (OpenAI)
- Key specs: 128K context, $75/$150 per 1M tokens, multimodal.
- Strengths: 27% faster reasoning vs. GPT-4; low hallucination rate (37.1%).
- Claude 3.7 Sonnet (Anthropic)
- Key specs: 200K context, $3/$15 per 1M tokens, 70.3% SWE-bench.
- Strengths: Balanced speed/accuracy; ideal for customer support.
- OpenAI o4-mini (OpenAI)
- Key specs: 200K context, $1.1/$4.4 per 1M tokens, 93.4% AIME.
- Strengths: Budget reasoning model; 10x cheaper than GPT-4.5.
Open-Source Models (Self-Hostable)
- Llama 4 Scout (Meta)
- Key specs: 10M token context (largest ever), Apache 2.0 license, multimodal.
- Strengths: Processes entire codebooks/legal docs; runs on 1 GPU.
- Popularity: Most forked OSS model; used by 90K+ firms.
- DeepSeek-R1 (DeepSeek)
- Key specs: 128K context, 671B MoE (37B active), $0.55/$2.19 per 1M tokens.
- Strengths: #1 open model on Chatbot Arena; top math/coding performance.
- Llama 4 Maverick (Meta)
- Key specs: 1M context, 400B params, Apache 2.0.
- Strengths: Multilingual (200+ languages); vision + text fusion.
- Qwen 3 (Alibaba)
- Key specs: 235B params, 32K context, Apache 2.0 license.
- Strengths: Trilingual (EN/CN/JP); beats GPT-4o in efficiency.
- Mistral Small 3 (Mistral AI)
- Key specs: 24B params, 128K context, $0.40/$2.0 per 1M tokens.
- Strengths: 3x faster than Llama 3.3; runs on laptops.
- Command R+ (Cohere)
- Key specs: 128K context, RAG-optimized, 10-language support.
- Strengths: Enterprise document QA; cites sources.
- Gemma 3 (Google)
- Key specs: 27B params, 128K context, free for commercial use.
- Strengths: On-device deployment; ideal for edge AI.
- Mixtral 8x22B (Mistral AI)
- Key specs: 141B params (39B active), 64K context, Apache 2.0.
- Strengths: Multilingual math/coding; function calling.
📊 Key Trends Driving Popularity (2025)
- Reasoning Over Scale: Claude 4 Opus and Gemini 2.5 Pro use “chain-of-thought” to solve complex problems methodically.
- Mega-Context Windows: Llama 4 Scout (10M tokens) and Gemini 2.5 Pro (1M tokens) enable book-length analysis.
- Cost Revolution: Mistral Small 3 and o4-mini deliver 90% of premium performance at 8x lower cost.
- Real-Time Data: Grok-3 and Gemini 2.5 Flash integrate live web/search tools.
- Open-Source Surge: 92% of Fortune 500 firms now use OSS models for customization.
For live benchmark comparisons (e.g., coding vs. reasoning), see:
→ Vellum LLM Leaderboard
→ LLM Stats
