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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.
LEP-AD
🇺🇸 King Abdullah University of Science and Technology (KAUST)
Claude
🇺🇸 Anthropic
Alpaca
🇺🇸 Stanford University
Pythia-Chat-Base-7B-v0.16
🇺🇸 Together
Flan UL2
🇺🇸 Google Brain
Consistency Model (CIFAR-10)
🇺🇸 OpenAI
DiT-XL/2
🇺🇸 New York University (NYU)
Palmyra Large 20B
🇺🇸 Writer
CodeGen-Mono 16.1B
🇺🇸 Salesforce
LLaMA-13B
🇺🇸 Meta AI
LLaMA-33B
🇺🇸 Meta AI
LLaMA-65B
🇺🇸 Meta AI
LLaMA-7B
🇺🇸 Meta AI
Hyena 1.3B
🇺🇸 Stanford University
Hyena-2 153M
🇺🇸 Stanford University
Hyena-2 355M
🇺🇸 Stanford University
Hyena-3-slim
🇺🇸 Stanford University
Anthropic LM 175B
🇺🇸 Anthropic
ControlNet
🇺🇸 Stanford University
ProteinDT
🇺🇸 University of California (UC) Berkeley
ToolFormer
🇺🇸 Meta AI
ProteinSGM
🇺🇸 University of Toronto
CD-GraB (WT2)
🇺🇸 Cornell University
Chemistry42
🇺🇸 Insilico Medicine AI
KeAP
🇺🇸 The University of Hong Kong
Genie-SCOPe (bio)
🇺🇸 Columbia University
Protst
🇺🇸 Mila - Quebec AI (originally Montreal Institute for Learning Algorithms)
RESP AI
🇺🇸 University of California San Diego
MoLFormer-XL
🇺🇸 IBM
GPT-2+Active-SGD (WT2)
🇺🇸 University of Montreal / Université de Montréal
Operator
🇺🇸 OpenAI
Ankh_base
🇺🇸 Technical University of Munich
Ankh_large
🇺🇸 Technical University of Munich
Nucleotide Transformer
🇺🇸 NVIDIA
SantaCoder
🇺🇸 Hugging Face
SparseOPT-13B
🇺🇸 Institute of Science and Technology Austria (ISTA)
SparseOPT-175B
🇺🇸 Institute of Science and Technology Austria (ISTA)
SparseOPT-30B
🇺🇸 Institute of Science and Technology Austria (ISTA)
SparseOPT-66B
🇺🇸 Institute of Science and Technology Austria (ISTA)
Hybrid H3-1.3B
🇺🇸 Stanford University
Hybrid H3-125M
🇺🇸 Stanford University
Hybrid H3-2.7B
🇺🇸 Stanford University
Hybrid H3-355M
🇺🇸 Stanford University
OPT-IML (175B)
🇺🇸 Meta AI
CaLM
🇺🇸 University of Oxford
text-embedding-ada-002
🇺🇸 OpenAI
TranceptEve
🇺🇸 University of Oxford
Stable Diffusion 2.1
🇺🇸 Stability AI
Transformer + GFM
🇺🇸 Nanjing University
GPT-3.5 Turbo
🇺🇸 OpenAI
GPT-3.5
🇺🇸 OpenAI
scFormer
🇺🇸 University of Toronto
Galactica
🇺🇸 Meta AI
Innovative Drug-like Molecule Generation from
🇺🇸 University of Pittsburgh
BLOOMZ-176B
🇺🇸 Hugging Face
mT0-13B
🇺🇸 Hugging Face
eDiff-I
🇺🇸 NVIDIA
GearNet
🇺🇸 Mila - Quebec AI (originally Montreal Institute for Learning Algorithms)
Transformer-XL + PowerSGD + L-Greco
🇺🇸 Institute of Science and Technology Austria (ISTA)
MIF-ST
🇺🇸 Microsoft Research
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.