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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 โ GPT, Claude, Gemini, Llama, Mistral, Qwen and 400+ more โ with parameter counts, context windows, benchmark scores and provider pricing.
Coconut
๐บ๐ธ Facebook
Gemini 2.0 Flash
๐บ๐ธ Google DeepMind
Gemini 2.0 Pro
๐บ๐ธ Google DeepMind
T-Lite
๐ท๐บ T-Bank
T-Pro
๐ท๐บ T-Bank
EXAONE 3.5 2.4B
๐ฐ๐ท LG AI Research
EXAONE 3.5 32B
๐ฐ๐ท LG AI Research
EXAONE 3.5 7.8B
๐ฐ๐ท LG AI Research
Grok Image Generation / Aurora
๐บ๐ธ xAI
Llama 3.3 70B
๐บ๐ธ Meta AI
Infinity
๐จ๐ณ ByteDance
Pleias 1.0 1.2B
๐ซ๐ท PleIAs
Pleias 1.0 350m
๐ซ๐ท PleIAs
o1
๐บ๐ธ OpenAI
TokenFlow-t2i
๐จ๐ณ ByteDance
voyage-code-3
๐บ๐ธ Voyage AI
Amazon Nova Canvas
๐บ๐ธ Amazon
Amazon Nova Micro
๐บ๐ธ Amazon
Luma Photon
๐บ๐ธ LumaLabs
Luma Photon Flash
๐บ๐ธ LumaLabs
Poolside Malibu
๐บ๐ธ Poolside
Gemma 2 9B Neogenesis ITA
๐ฎ๐น anakin87
RNAformer
๐ฉ๐ช University of Freiburg
360gpt2-pro
๐จ๐ณ 360 Security Technology
HaiYue (ๆตชๆฝฎ้็จ่ฝฏไปถๆ้ๅ ฌๅธ)
๐จ๐ณ Inspur
INTELLECT-1
๐บ๐ธ Prime Intellect
MiLi (็ฑณ็ฒ)
๐จ๐ณ CreditEase
Mingzhi Guwen
๐จ๐ณ "Shanghai Shuheng Information Technology Co.
abab7
๐จ๐ณ MiniMax
DeepThought-8B
๐ฌ๐ง Ruliad
ControlNet (SD 3.5 Large) Blur
๐บ๐ธ Stability AI
ControlNet (SD 3.5 Large) Canny
๐บ๐ธ Stability AI
ControlNet (SD 3.5 Large) Depth
๐บ๐ธ Stability AI
ConfRank
๐ฉ๐ช University of Bonn
Hymba
๐บ๐ธ NVIDIA
Tulu 3 (Tรผlu 3) 70B
๐บ๐ธ Allen Institute for AI
Tulu 3 8B
๐บ๐ธ Allen Institute for AI
DeepSeek-R1-Lite-Preview
๐จ๐ณ DeepSeek
Boltz-1
๐บ๐ธ Massachusetts Institute of Technology (MIT)
360Zhinao2-7B
๐จ๐ณ 360 Security Technology
BiRNA-BERT
๐บ๐ธ Bangladesh University of Engineering and Technology
SK Telecom Telco
๐ฐ๐ท SK Telecom
k0-math
๐จ๐ณ Moonshot
Gemini-Exp-1114
๐บ๐ธ Google DeepMind
LLaVA-CoT
๐จ๐ณ Peking University
Mistral Large 2.1
๐ซ๐ท Mistral AI
Qwen2.5-Turbo
๐จ๐ณ Qwen
bailing-pro-1120
๐จ๐ณ Ant Group
Athene-V2
๐บ๐ธ Nexusflow
Gemma2 9B CPT Sahabat-AI
๐ฎ๐ณ Indosat
Qwen2.5-Coder (32B)
๐จ๐ณ Qwen
MassiveFold
๐ซ๐ท Universitรฉ de Lille
stFormer
๐บ๐ธ Shanghai Jiao Tong University
TeleChat2-3B
๐จ๐ณ China Telecom
TeleChat2-7B
๐จ๐ณ China Telecom
Mistral Moderation
๐ซ๐ท Mistral AI
FLUX1.1 [pro] Raw
๐ฉ๐ช Black Forest Labs
FLUX1.1 [pro] Ultra
๐ฉ๐ช Black Forest Labs
Hunyuan-Large
๐จ๐ณ Tencent
OpenPhenom-S/16
๐บ๐ธ Recursion Pharmaceuticals
About Large language models (LLMs)
Large language models (LLMs) are the foundation of modern generative AI โ 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 โ 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 โ 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.