Compare large language models from OpenAI, Anthropic, Google, xAI and more. Find context windows, reasoning capabilities, benchmarks, and pricing for GPT-5, Claude 4, Gemini 3, and Grok 4.
GPT-4.1 excels at instruction following and tool calling, with broad knowledge across domains. Featu...
Flagship model optimized for coding and agentic tasks with configurable reasoning effort.
Faster, cost-efficient version of GPT-5 suitable for well-defined tasks and precise prompts.
Fastest, most cost-efficient version of GPT-5, ideal for summarization and classification tasks.
The best model in the world for multimodal understanding, and our most powerful agentic and vibe-cod...
Claude Sonnet 4.5 is the best coding model in the world. It's the strongest model for building compl...
A frontier multimodal model optimized specifically for high-performance agentic tool calling.
284B parameter (13B activated) Mixture-of-Experts language model with 1M token context length. Featu...
31B-parameter (3B active) Mamba2-Transformer hybrid MoE multimodal model that unifies video, audio, ...
30.7B-parameter dense multimodal model from Google DeepMind with 256K token context. Handles text, i...
25.2B total parameter (3.8B active) Mixture-of-Experts model with 256K token context. 8 active exper...
4.5B effective parameter (8B with Per-Layer Embeddings) on-device model with 128K token context. Sup...
8B-parameter end-to-end unified multimodal model based on NEO-Unify architecture. Native unified tex...
Selecting the right language model depends on your specific use case, budget, and performance requirements. Compare key factors like context window, reasoning capabilities, and multimodal support.
Larger windows (up to 1M tokens) enable processing entire documents, codebases, or long conversations without chunking.
Models with reasoning spend more time analyzing complex problems. Ideal for coding, math, and step-by-step analysis.
Text-only models are faster and cheaper. Multimodal models (vision, audio) enable richer interactions but cost more.
Input tokens are typically cheaper than output. Consider caching discounts and batch API options for high-volume use.
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Our LLM comparison page helps you evaluate hundreds of models including GPT, Claude, Gemini, DeepSeek V4, and Meta's Llama family. Compare context windows, pricing per million tokens for both input and output, and supported modalities. Newer models like Gemma 4 with its 31B parameter variant and Nemotron 3 Nano Omni offer compelling alternatives to established players, and our side-by-side comparison makes evaluating these trade-offs straightforward.
Whether you need a model for chat, code generation, analysis, or creative tasks, comparing LLMs by benchmark performance, context window size, and pricing helps you choose wisely. GPUvec breaks down each model's capabilities including multimodal support for text, image, audio, and video input and output. Models like DeepSeek V4 Flash, Gemini 3.5 Flash, and Grok 4 each excel in different areas, and understanding these differences is key to building cost-effective AI applications.
LLM pricing varies dramatically between providers and models. Compare input and output token prices from OpenAI, Anthropic (Claude), Google (Gemini), xAI (Grok), and open-source options. Understanding the pricing structure of each provider helps you budget accurately for your AI applications whether you are deploying chatbots, building RAG pipelines, or generating content at scale.