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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.
LSTM-MemoryAug (PTB)
🇺🇸 Johns Hopkins University
LSTM-MemoryAug (WT2)
🇺🇸 Johns Hopkins University
PAR Transformer Large
🇺🇸 NVIDIA
ProBERTa
🇺🇸 University of Illinois Urbana-Champaign (UIUC)
ESM1-43M
🇺🇸 Facebook AI Research
ESM1-670M (UR100)
🇺🇸 Facebook AI Research
ESM1-670M (UR50/D)
🇺🇸 Facebook AI Research
ESM1-670M (UR50/S)
🇺🇸 Facebook AI Research
ESM1-85M
🇺🇸 Facebook AI Research
Transformer+Recurrent Windows of Context
🇺🇸 Toyota Technological Institute at Chicago
ERNIE-GEN (large)
🇨🇳 Baidu
DeLighT
🇺🇸 University of Washington
mBART-50
🇺🇸 Facebook AI
Grown to Prune Two-layer stacked LSTM
🇺🇸 University of Chicago
GPT2-LayerFusion-WS
🇺🇸 University of Liverpool
TransformerXL-LayerFusion-CA
🇺🇸 University of Liverpool
Hopfield Networks (2020)
🇦🇹 Johannes Kepler University Linz
DLRM-2021
🇺🇸 Meta AI
GShard (600B)
GShard (dense)
GPT-3 13B
🇺🇸 OpenAI
GPT-3 2.7B
🇺🇸 OpenAI
GPT-3 6.7B
🇺🇸 OpenAI
GPT-3 Large
🇺🇸 OpenAI
GPT-3 Medium
🇺🇸 OpenAI
GPT-3 Small
🇺🇸 OpenAI
GPT-3 XL
🇺🇸 OpenAI
iGPT-L
🇺🇸 OpenAI
3-Layer-Tensor-Transformer+AdaHessian
🇺🇸 University of California (UC) Berkeley
6-Layer-Tensor-Transformer+AdaHessian
🇺🇸 "NERSC
GPT-3 175B (davinci)
🇺🇸 OpenAI
GPT3-6.7B (rerun of original)
🇺🇸 Microsoft
Retrieval-Augmented Generator
rTop-k(distributed setting)
🇺🇸 Stanford University
Specter
🇺🇸 Allen Institute for AI
ONLSTM-SYD
🇨🇳 Westlake University
NAS+ESS (156M)
🇨🇳 Northeastern University (China)
NAS+ESS (23M)
🇨🇳 Northeastern University (China)
UnifiedQA
🇺🇸 Allen Institute for AI
Segatron XL base, M=384
🇺🇸 University of Waterloo
Segatron XL large, M=384
🇺🇸 University of Waterloo
DiffStk-MRNN
🇺🇸 Pennsylvania State University
GePpeTto
🇮🇹 ILC-CNR
AraBERT
🇱🇧 American University of Beirut
AraBERT LArge v2
🇱🇧 American University of Beirut
MetNet
ELECTRA
🇺🇸 Stanford University
Tensor-Transformer(1core)+PN (PTB)
🇺🇸 University of California (UC) Berkeley
Tensor-Transformer(1core)+PN (WT103)
🇺🇸 University of California (UC) Berkeley
WDC20 / DLWP
🇺🇸 University of Washington
ProGen
🇺🇸 Salesforce Research
Local Transformer (WT103)
🇺🇸 Google Research
Routing Transformer (WT-103)
🇺🇸 Google Research
TransformerXL + spectrum control
🇺🇸 University of California Los Angeles (UCLA)
MuPIPR
🇺🇸 University of California Los Angeles (UCLA)
LSTM-3-layer+Gadam
🇺🇸 University of Oxford
TCAN (PTB)
🇨🇳 Ant Group
TCAN (WT2)
🇺🇸 Nanjing University
Feedback Transformer
🇺🇸 LORIA
FFN SwiGLU
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.