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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.
Doubao Seed 2.1
🇨🇳 ByteDance
Baichuan-M4
🇨🇳 Baichuan
GPT-5.5-Cyber
🇺🇸 OpenAI
PLaMo 3.0 Prime
🇯🇵 Preferred Networks
Sakana Fugu
🇯🇵 Sakana AI
GLM-5.2
🇨🇳 Zhipu AI
DiffusionGemma 26B-A4B
🇺🇸 Google DeepMind
NVIDIA Nemotron 3 Ultra
🇺🇸 NVIDIA
MAI-Thinking-1
🇺🇸 Microsoft
LFM2.5-8B-A1B
🇺🇸 Liquid AI
Qwen3.7-Max
🇨🇳 Qwen
SkyClaw-v1.0
🇨🇳 Skywork
Domyn Small
🇮🇹 Domyn
ERNIE 5.1
🇨🇳 Baidu
GPT-5.5 Instant
🇺🇸 OpenAI
IBM Granite 4.1
🇺🇸 IBM
FastwebMIIA 7B (2026)
🇮🇹 Fastweb
nesso 0.4B Agentic
🇮🇹 mii-llm
nesso 0.4B Instruct
🇮🇹 mii-llm
nesso 4B
🇮🇹 mii-llm
Seed Prover 1.5
🇨🇳 ByteDance
ERNIE-5.0-Preview-1203
🇨🇳 Baidu
MiniMax-M2.1
🇨🇳 MiniMax
GLM-4.7
🇨🇳 Zhipu AI
Grok Collections API
🇺🇸 xAI
Seed1.8
🇨🇳 ByteDance
gemini-3-flash-preview
🇺🇸 Google DeepMind
Seedance 1.5 pro
🇨🇳 ByteDance
Nemotron 3 Nano
🇺🇸 NVIDIA
OLMo 3.1 32B Instruct
🇺🇸 Allen Institute for AI
OLMo 3.1 32B Think
🇺🇸 Allen Institute for AI
AutoGLM-Phone-Multilingual
🇨🇳 Zhipu AI
GPT-5.2
🇺🇸 OpenAI
GLM-ASR-2512
🇨🇳 Zhipu AI
ERNIE-5.0-Preview-1103
🇨🇳 Baidu
Hunyuan 2.0 (Think & Instruct)
🇨🇳 Tencent
Amazon Nova 2 Lite
🇺🇸 Amazon
Amazon Nova 2 Pro (Preview)
🇺🇸 Amazon
DeepSeek-V3.2
🇨🇳 DeepSeek
DeepSeek-V3.2-Speciale
🇨🇳 DeepSeek
Devstral Small 2
🇫🇷 Mistral AI
Mistral Small Creative
🇫🇷 Mistral AI
Claude Opus 4.5
🇺🇸 Anthropic
ERNIE-5.0-Preview-1120
🇨🇳 Baidu
OLMo 3 (family)
🇺🇸 Allen Institute for AI
Grok 4.1 Fast
🇺🇸 xAI
gemini-3-pro-preview
🇺🇸 Google DeepMind
Grok 4.1
🇺🇸 xAI
ERNIE-5.0-Preview-1022
🇨🇳 Baidu
Kimi K2 Thinking
🇨🇳 Moonshot
Lara Think
🇮🇹 Translated
Kimi Linear
🇨🇳 Moonshot
Composer
🇺🇸 Cursor
SWE-1.5
🇺🇸 Cognition
Nemotron Nano 12B V2 VL
🇺🇸 NVIDIA
Tongyi DeepResearch
🇨🇳 Alibaba-NLP
LoongRL 14B
🇺🇸 Microsoft Research Asia
LoongRL 7B
🇺🇸 Microsoft Research Asia
MiniMax-M2
🇨🇳 MiniMax
Ring-flash-linear-2.0
🇨🇳 Ant Group
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.