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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.
o1-mini
🇺🇸 OpenAI
o1-preview
🇺🇸 OpenAI
CPDiffusion
🇺🇸 Shanghai Jiao Tong University
GenMS
🇺🇸 Google DeepMind
KinoML
🇺🇸 Charité-Universitätsmedizin Berlin
MolPhenix
🇺🇸 Valence Labs
AbGPT
🇺🇸 Carnegie Mellon University (CMU)
MMAPLE
🇺🇸 City University of New York
VespaG
🇺🇸 Technical University of Munich
Aristotle
🇺🇸 Harmonic
MPDF
🇺🇸 Chinese University of Hong Kong (CUHK)
ProtSSN
🇺🇸 Shanghai Jiao Tong University
SAAMBE-MEM
🇺🇸 Clemson University
xLAM-8x22B
🇺🇸 Salesforce
AlphaProteo
🇺🇸 Google DeepMind
EnOpt
🇺🇸 University of Pittsburgh
µFormer
🇺🇸 Microsoft Research AI for Science
CHIEF
🇺🇸 Harvard Medical School
OLMoE
🇺🇸 Allen Institute for AI
Alphaflow
🇺🇸 Massachusetts Institute of Technology (MIT)
DTI-LM
🇺🇸 University of Central Florida
ESMFlow
🇺🇸 Massachusetts Institute of Technology (MIT)
ParetoDrug
🇺🇸 Chinese University of Hong Kong (CUHK)
NV-Embed-v2
🇺🇸 NVIDIA
DrugFormer
🇺🇸 University of Florida
GLA Transformer 1.3B
🇺🇸 MIT-IBM Watson AI Lab
GLA Transformer 340M
🇺🇸 MIT-IBM Watson AI Lab
DISTRO
🇺🇸 Nous Research
Xinyu
🇺🇸 Zhejiang University (ZJU)
GITIII
🇺🇸 Yale School of Public Health
AntiFormer
🇺🇸 University of Florida
Hybrid-Phi-Mamba-1.5B
🇺🇸 Carnegie Mellon University (CMU)
TransFew
🇺🇸 University of Missouri
CLR_ESP
🇺🇸 Kansas State University
Transformers in music recommendation
🇺🇸 Google Research
Hermes 3 405B
🇺🇸 Nous Research
Hermes 3 70B
🇺🇸 Nous Research
Hermes 3 8B
🇺🇸 Nous Research
Agent Q
🇺🇸 Stanford University
Grok-2
🇺🇸 xAI
Grok-2 mini
🇺🇸 xAI
PepMLM
🇺🇸 Duke University
EPInformer
🇺🇸 The University of Hong Kong
Midjourney V6.1
🇺🇸 Midjourney
AFM-on-device
🇺🇸 Apple
AFM-server
🇺🇸 Apple
ProRNA3D-Single
🇺🇸 Virginia Tech (Virginia Polytechnic Institute and State University)
SaulLM-large
🇺🇸 Equall.ai
AlphaGeometry 2
🇺🇸 Google DeepMind
AlphaProof
🇺🇸 Google DeepMind
SearchGPT
🇺🇸 OpenAI
Palmyra Fin
🇺🇸 Writer
Palmyra Med
🇺🇸 Writer
PrePR-CT
🇺🇸 King Abdullah University of Science and Technology (KAUST)
Llama 3.1-405B
🇺🇸 Meta AI
Llama 3.1-70B
🇺🇸 Meta AI
Llama 3.1-8B
🇺🇸 Meta AI
PepPrCLIP
🇺🇸 Duke University
DCLM 7B
🇺🇸 Apple
Athene-70B
🇺🇸 Nexusflow
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.