Excels at deep reasoning, complex coding, and autonomous agent workflows with sustained performance, extended thinking, tool use, and memory across tasks.

Balances intelligence with efficiency for coding, research, and automation tasks; excels in reasoning, content generation, and nuanced instruction following.

Excels at building interactive web apps, advanced code editing and agentic workflows, with native multimodality and strong video-to-code capabilities.

MoE model with 22B active parameters featuring dual thinking modes for complex reasoning and efficient conversation across 100+ languages.

MoE architecture with 3.3B active parameters, balancing efficiency with strong reasoning, multilingual capabilities, and specialized thinking mode.

A thinking model offering enhanced reasoning with controllable "thinking" capabilities, balancing speed, cost, and performance for developers.

Optimized for fast, affordable reasoning with strong coding and visual skills, large 200k-token context, and efficient handling of complex tasks.

Excels at advanced reasoning, coding, math, and visual tasks with simulated reasoning, tool use, web browsing, and image understanding integration.

OpenAI's fastest, cost-effective model with full 1 million token context, optimized for classification, autocompletion, and real-time AI agent tasks.

Powerful mid-sized model with GPT-4o-level performance at lower cost and latency, featuring a 1 million token context window for complex tasks.

Excels in coding and instruction following with million-token context window, enabling superior performance on complex, multi-step tasks.

Multimodal model with 17B active parameters, excelling at text, image, code, and multilingual tasks. Supports 1M-token context for advanced enterprise use.

Efficient multimodal MoE model with 10M-token context, excelling at multi-document analysis, codebase reasoning, and image understanding across 12 languages.

Multimodal model with 10M-token context, efficient MoE design, and strong performance in text, image, code, and multilingual reasoning tasks.

Multimodal model with 400B parameters, 128 experts, and 1M context; excels at multilingual text/image reasoning, coding, and enterprise-scale applications.

Delivers advanced reasoning, code generation, and mathematical skills, processes long inputs efficiently, and accelerates results with innovative Mixture-of-Experts design.

A lightweight, versatile 24B multimodal model handling text and images with extensive multilingual support and 128k token context window.

Gemma 3 has a large, 128K context window, multilingual support in over 140 languages, and is available in more sizes than previous versions. Gemma 3 models are well-suited for a variety of text generation and image understanding tasks, including question answering, summarization, and reasoning.

Google's most powerful Gemini 2.0 model, released in Feburary, 2025

Performs exhaustive, multi-step research by autonomously searching and synthesizing hundreds of sources into detailed, expert-level reports across domains.

Premium reasoning model for complex, multi-step analysis. Delivers detailed explanations, real-time web search, and double citations for thorough answers.

Reasoning-focused LLM excelling in complex tasks like math and coding. Matches larger models' performance while running efficiently on consumer hardware.

A hybrid reasoning model with standard and extended thinking modes, delivering twice the speed and exceptional performance in coding and problem-solving tasks.

Fast reasoning model with real-time web search, chain-of-thought capabilities, and citation support. Excels at complex queries with quick, accurate responses.

Optimized for search-augmented tasks, delivering fast, accurate answers with real-time web data and detailed citations. Excels in research and fact-checking.

Excels at complex, multi-step queries with real-time web search, detailed answers, extensive citations, and customizable information retrieval.

Employs a massive Mixture-of-Experts architecture and Multi-Layer Attention to deliver advanced, polished reasoning and problem-solving across math, code, and more.

Excels at step-by-step reasoning and code generation, delivering transparent, structured answers through reinforcement learning and Mixture of Experts.

An open-source reasoning model using Mixture-of-Experts architecture, delivering powerful math and code capabilities comparable to OpenAI's o1.

Excels at efficient reasoning and code generation, leveraging large-scale mixture-of-experts architecture with advanced multi-token prediction and training innovations.

Powers advanced reasoning, code generation, and multilingual tasks with efficient MoE architecture and enhanced multi-token prediction for faster, optimized results.

Advanced agentic capabilities, roleplaying, reasoning, multi-turn conversation, long context coherence, and code generation with structured outputs.

Advanced agentic capabilities with strong roleplaying, reasoning, and structured output generation for technical tasks.

Optimized for dialogue with strong reasoning, multilingual support, and efficient performance approaching larger models.

Optimized for speed via speculative decoding, excels in reasoning, coding, and complex tasks while maintaining high efficiency.

Excels in question answering, reasoning, and code generation, with use cases including synthetic data creation and evaluating smaller model outputs.

This experimental model excels in math, coding, and scientific reasoning, developed by Alibaba's Qwen Team to advance AI analytical capabilities.

Specialized in advanced reasoning and problem-solving, excelling in mathematics and programming with a 32B parameter transformer architecture.

Specializes in code generation, reasoning, and fixing across 40+ languages, matching GPT-4o's coding capabilities with 128k token context.

Specializes in code generation, reasoning, and fixing with 128K token context, open-source licensing, and local deployment capabilities.

Lightweight model optimized for edge/mobile devices, excels in multilingual retrieval and summarization tasks with real-time processing and enhanced privacy.

Multilingual dialogue model optimized for tool integration and safety, with 128K context length for extended interactions.

Powerful AI with exceptional coding abilities, twice the speed of previous versions, and advanced reasoning for complex software development tasks.

Anthropic's fastest model offering advanced coding, tool use, and reasoning capabilities with rapid response times for real-time applications and personalized experiences.

Efficient edge model with native function calling and interleaved sliding-window attention for fast, memory-efficient processing in resource-constrained environments.

Customized by NVIDIA to enhance helpfulness, this model excels in instruction-following tasks through human preference alignment and improved response relevance.

Efficient for mobile/edge devices, excels in text summarization, classification, and translation. Ideal for AI writing assistants and customer service applications.

Optimized for multilingual instruction-following tasks, balancing efficiency and performance in dialogue, summarization, and agentic applications with 3B parameters and scalable architecture.

Optimized for high-volume, cost-effective tasks with multimodal input support, excelling in transcription and long-context processing.

Instruction-tuned LLM excelling in long-context processing (131K tokens), multilingual support (29+ languages), and structured data handling.

Optimized for coding and math with Chain-of-Thought reasoning, offering fast, cost-efficient responses for complex problem-solving.

Reasoning-focused LLM for complex science, math, and coding tasks, generating detailed thought processes before responses.

Multimodal model handling text and images at native resolution with 128K context window, excelling in visual reasoning tasks like document analysis and image captioning.

Advanced agentic capabilities with enhanced reasoning, roleplaying, and multi-turn conversation handling. Excels in structured output and long-context coherence.

Multilingual LLM excelling in question answering, reasoning, code generation, and synthetic data generation.

Excels in multilingual tasks, tool use, coding, and reasoning with improved accuracy and efficient performance.

Excels in multilingual dialogue and long-form text processing with strong reasoning for conversational agents and coding assistance.

Optimized for multilingual dialogue with 128k context length, excels in chat, text generation, and language translation.

Optimized for multilingual dialogue with 128k context, instruction-tuned via SFT/RLHF, and enhanced with synthetic data for safety and performance.

Instruction-tuned LLM excelling in multilingual dialogue, synthetic data generation, and model distillation with 131k token context for complex tasks.

Optimized for multilingual dialogue and long-context tasks, this model excels in production-scale applications with advanced inference capabilities and a 128k token context window.

Handles long-form content with 128k token context, excels in multilingual tasks, coding, and function calling via natural language.

Cost-efficient, fast model with 128K context window, supporting text/vision inputs and improved multilingual performance.

Efficient 9B parameter model trained on diverse web, code, and math data, excelling in coding and mathematical tasks.

Specializes in code generation with 32k token context, excelling in completion, debugging, and optimization across 80+ languages.

Multimodal LLM with 2M token context, excels in complex reasoning, coding, and multimodal Q&A across text, images, audio, and video.

Optimized for speed and efficiency, handles high-volume tasks with multimodal processing (text, images, video, audio) for summarization, chat, and data extraction.

Multimodal LLM for real-time text, audio, and visual processing with multilingual support, emotional audio responses, and image generation.

Efficient Sparse MoE architecture with 39B active parameters, excels in multilingual tasks, math, coding, and handles 64K token contexts.

Powerful LLM with 123B parameters, excelling in multilingual tasks, coding, and reasoning, optimized for single-node inference and long-context applications.

Efficient Mixture of Experts (8 experts) with 13B active parameters, optimized for multilingual tasks and cost-performance balance.

Balanced performance in natural language and code tasks, efficiently handling longer sequences with innovative attention mechanisms.

Optimized for STEM reasoning and problem-solving, excelling in complex tasks like advanced math and coding with improved cost efficiency.

Delivers strong mathematical and coding abilities, matching the performance of larger models while using efficient distillation and multilingual support.

Specializes in complex reasoning through chain-of-thought processing, excelling in STEM tasks like coding, math, and scientific analysis.

Excels in natural conversation and creative tasks with improved emotional intelligence and multilingual support, prioritizing intuitive interactions over structured reasoning.

Optimized for edge computing with function-calling capabilities, excelling in knowledge retrieval and commonsense reasoning with 128k token context.

Cost-efficient, budget-friendly multimodal LLM for real-time tasks with 1M token input context and enhanced performance.

Multimodal LLM for agentic applications, handling real-time data integration and multi-step tasks with enhanced reasoning via Thinking Mode, integrating Google tools and third-party functions.

Specializes in coding tasks with multilingual support for 80+ languages, excelling in code generation, fill-in-the-middle, and test creation with a 256K token context.

Handles complex reasoning and coding tasks, generates and interprets multimodal content, and supports interactive visualizations with an extensive 1M token context.