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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.
CodonTransformer
🇺🇸 Vector Institute
IDPFold
🇨🇳 Shandong University
JURA Bio Model
🇺🇸 JURA Bio
Novae
🇫🇷 CentraleSupelec
Text2Protein
🇺🇸 University of California San Diego
4D Diffusion for Dynamic Protein Structure Prediction with Reference Guided Motion Alignment
🇨🇳 Fudan University
DataGemma
o1-mini
🇺🇸 OpenAI
o1-preview
🇺🇸 OpenAI
Automated design of multi-target ligands by generative deep learning
🇩🇪 Goethe University Frankfurt
Solar Pro
🇰🇷 Upstage
CPDiffusion
🇺🇸 Shanghai Jiao Tong University
GenMS
🇺🇸 Google DeepMind
KinoML
🇺🇸 Charité-Universitätsmedizin Berlin
MolPhenix
🇺🇸 Valence Labs
AbGPT
🇺🇸 Carnegie Mellon University (CMU)
BetterBodies
🇩🇪 University of Freiburg
DiffForce
🇨🇳 University of Cambridge
ESMIF-DDG
🇬🇧 Peptone
EpiScan
🇨🇳 Sun Yat-sen University
MMAPLE
🇺🇸 City University of New York
PDFII
🇨🇳 Sichuan University
ProteinMPNN-DDG
🇬🇧 Peptone
VespaG
🇺🇸 Technical University of Munich
RiboCode
🇨🇳 Sun Yat-sen University
Aristotle
🇺🇸 Harmonic
DDGemb
🇮🇹 University of Bologna
ESM-DBP
🇨🇳 Hunan University
MPDF
🇺🇸 Chinese University of Hong Kong (CUHK)
DeepSeek-V2.5
🇨🇳 DeepSeek
GearBind
🇨🇳 BioGeometry
MiniCPM3.0
🇨🇳 Mianbi Intelligence
ProtSSN
🇺🇸 Shanghai Jiao Tong University
SAAMBE-MEM
🇺🇸 Clemson University
xLAM-8x22B
🇺🇸 Salesforce
AlphaProteo
🇺🇸 Google DeepMind
EnOpt
🇺🇸 University of Pittsburgh
Hunyuan Turbo
🇨🇳 Tencent
µFormer
🇺🇸 Microsoft Research AI for Science
CHIEF
🇺🇸 Harvard Medical School
Integrating Deep Learning and Synthetic Biology: A Co-Design Approach for Enhancing Gene Expression via N-Terminal Coding Sequences
🇨🇳 National University of Singapore
MolMVC
🇨🇳 Central South University
DrugCLIP
🇨🇳 Tsinghua University
OLMoE
🇺🇸 Allen Institute for AI
Alphaflow
🇺🇸 Massachusetts Institute of Technology (MIT)
ChatMol
🇨🇳 Tsinghua University
DTI-LM
🇺🇸 University of Central Florida
ESMFlow
🇺🇸 Massachusetts Institute of Technology (MIT)
ParetoDrug
🇺🇸 Chinese University of Hong Kong (CUHK)
Moonshot-v1
🇨🇳 Moonshot
HelixFold3
🇨🇳 Tecorigin LTD
NV-Embed-v2
🇺🇸 NVIDIA
RENNAISSANCE
🇨🇭 Ecole Polytechnique F´ed´erale de Lausanne (EPFL)
DrugFormer
🇺🇸 University of Florida
GLM-4-Plus
🇨🇳 Zhipu AI
Hairuo
🇨🇳 Inspur
OPUS-Design
🇨🇳 Fudan University
Bielik-11B-v2
🇵🇱 SpeakLeash
GLA Transformer 1.3B
🇺🇸 MIT-IBM Watson AI Lab
GLA Transformer 340M
🇺🇸 MIT-IBM Watson AI Lab
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.