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Large language models (LLMs)
Browse every major large language model in one place. This LLM list tracks frontier and open-source foundation models — GPT, Claude, Gemini, Llama, Mistral, Qwen and 400+ more — with parameter counts, context windows, benchmark scores and provider pricing.
GPT-5.5-Cyber
🇺🇸 OpenAI
DiffusionGemma 26B-A4B
🇺🇸 Google DeepMind
NVIDIA Nemotron 3 Ultra
🇺🇸 NVIDIA
MAI-Thinking-1
🇺🇸 Microsoft
LFM2.5-8B-A1B
🇺🇸 Liquid AI
GPT-5.5 Instant
🇺🇸 OpenAI
IBM Granite 4.1
🇺🇸 IBM
Grok Collections API
🇺🇸 xAI
gemini-3-flash-preview
🇺🇸 Google DeepMind
Nemotron 3 Nano
🇺🇸 NVIDIA
OLMo 3.1 32B Instruct
🇺🇸 Allen Institute for AI
OLMo 3.1 32B Think
🇺🇸 Allen Institute for AI
GPT-5.2
🇺🇸 OpenAI
Amazon Nova 2 Lite
🇺🇸 Amazon
Amazon Nova 2 Pro (Preview)
🇺🇸 Amazon
Claude Opus 4.5
🇺🇸 Anthropic
OLMo 3 (family)
🇺🇸 Allen Institute for AI
Grok 4.1 Fast
🇺🇸 xAI
gemini-3-pro-preview
🇺🇸 Google DeepMind
Grok 4.1
🇺🇸 xAI
Composer
🇺🇸 Cursor
SWE-1.5
🇺🇸 Cognition
Nemotron Nano 12B V2 VL
🇺🇸 NVIDIA
LoongRL 14B
🇺🇸 Microsoft Research Asia
LoongRL 7B
🇺🇸 Microsoft Research Asia
Odyssey 1.2B
🇺🇸 Anthrogen
Odyssey 102B
🇺🇸 Anthrogen
Odyssey 12B
🇺🇸 Anthrogen
Claude Haiku 4.5
🇺🇸 Anthropic
Llama 4 Scout + ScaleRL
🇺🇸 Meta AI
MAI-Image-1
🇺🇸 Microsoft
C2S-Scale
🇺🇸 Google Research
Grok Imagine
🇺🇸 xAI
Gemini 2.5 Computer Use
Granite 4.0
🇺🇸 IBM
Granite-4.0-H-Micro
🇺🇸 IBM
Granite-4.0-H-Small
🇺🇸 IBM
Granite-4.0-H-Tiny
🇺🇸 IBM
Claude Sonnet 4.5
🇺🇸 Anthropic
Gemini 2.5 Flash (Sep 2025)
🇺🇸 Google DeepMind
Gemini 2.5 Flash-Lite (Sep 2024)
🇺🇸 Google DeepMind
SimpleFold
🇺🇸 Apple
Grok 4 Fast
🇺🇸 xAI
GPT‑5-Codex
🇺🇸 OpenAI
EmbeddingGemma
🇺🇸 Google DeepMind
Grok Code Fast 1
🇺🇸 xAI
Gemini 2.5 Flash Image (Nano Banana)
FlowER
🇺🇸 Massachusetts Institute of Technology (MIT)
Surya
🇺🇸 NASA
NVIDIA-Nemotron-Nano-12B-v2
🇺🇸 NVIDIA
NVIDIA-Nemotron-Nano-9B-v2
🇺🇸 NVIDIA
Nemotron Nano 9B v2
🇺🇸 NVIDIA
imagen 4 fast
🇺🇸 Google DeepMind
imagen 4 fast
Gemma 3 270M
🇺🇸 Google DeepMind
Claude Opus 4.1
🇺🇸 Anthropic
gpt-oss-120b
🇺🇸 OpenAI
gpt-oss-20b
🇺🇸 OpenAI
Gemini 2.5 Deep Think
rStar-Math (Qwen2-Math-7B base)
🇺🇸 Microsoft Research Asia
About Large language models (LLMs)
Large language models (LLMs) are the foundation of modern generative AI — general-purpose text models trained on vast corpora that can write, reason, summarise, translate and code. Choosing the best LLM is rarely about a single winner: the best AI model for one task may lag on another. Reasoning-heavy work rewards models that score well on benchmarks like MMLU, GPQA and AIME, while agentic and tool-use workloads care more about instruction following, function calling and long-context recall. When you compare LLMs, weigh raw capability against the practical constraints that decide cost and feasibility — context window, throughput, latency, licensing and price per million tokens. Open-source LLMs such as Llama, Qwen, Mistral and DeepSeek let you self-host and fine-tune, while proprietary frontier models from OpenAI, Anthropic and Google often lead on raw quality. Use our benchmarks to see where each model ranks, and put two candidates side by side with compare before you commit to a provider.
Frequently asked questions
What is the best LLM right now?
There is no single best LLM — it depends on the task. Frontier proprietary models from OpenAI, Anthropic and Google tend to lead on reasoning benchmarks, while open-source LLMs like Llama, Qwen and DeepSeek are best when you need to self-host or fine-tune. Compare candidates on the benchmarks page for your specific workload.
What is the best open source LLM?
The strongest open-source and open-weights LLMs at any given time typically come from the Llama, Qwen, Mistral and DeepSeek families. They can be downloaded, self-hosted and fine-tuned, and the top ones rival proprietary models on many benchmarks. Filter the list above by availability to see current open-weights options.
How do I compare two LLMs?
Use the compare tool to put two models side by side on parameters, context window, availability and benchmark scores, then check the benchmarks page for task-specific rankings such as MMLU, GPQA and coding scores.