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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.
Jaeger
🇩🇪 University Medicine Greifswald
Llama 3.2 1B
🇺🇸 Meta AI
Llama 3.2 3B
🇺🇸 Meta AI
MTDP
🇺🇸 Chinese University of Hong Kong (CUHK)
ProtBFN
🇬🇧 InstaDeep
Protein-Mamba
🇺🇸 Rensselaer Polytechnic Institute
Thermostable protein design
🇮🇳 "Indraprastha Institute of Information Technology Delhi"
dnaGrinder
🇺🇸 Hong Kong Polytechnic University
AMPLIFY
🇺🇸 Chandar Research Lab
PocketGen
🇨🇳 University of Science and Technology of China (USTC)
PreAlgPro
🇨🇳 Shanghai Ocean University
ProteinSetTransformer
🇺🇸 University of Wisconsin Madison
Spark 4.0
🇨🇳 iFlytek
TAWFN
🇨🇳 Northeastern University (China)
BTFBS
🇨🇳 Nanjing Agricultural University
IgGM
🇨🇳 Chinese Academy of Sciences
MoEFold2D
🇺🇸 George Washington University
PepINVENT
🇬🇧 AstraZeneca
ExSelfRL
🇨🇳 Soochow University
Prithvi WxC
🇺🇸 IBM Research
Telechat2-115B
🇨🇳 China Telecom
EITLEM-Kinetics
🇨🇳 Beijing University of Chemical Technology
GeoSeqBuilder
🇨🇳 Peking University
McMLP
🇺🇸 Harvard Medical School
Qwen2.5 Instruct (32B)
🇨🇳 Qwen
Qwen2.5 Instruct (72B)
🇨🇳 Qwen
Qwen2.5 Instruct (7B)
🇨🇳 Qwen
Qwen2.5-1.5B
🇨🇳 Qwen
Qwen2.5-14B
🇨🇳 Qwen
Qwen2.5-3B
🇨🇳 Qwen
Qwen2.5-72B
🇨🇳 Qwen
Qwen2.5-7B
🇨🇳 Qwen
Qwen2.5-Math-1.5B
🇨🇳 Qwen
Qwen2.5-Math-7B-Base
🇨🇳 Qwen
pKALM
🇯🇵 Hokkaido University
AtomFlow
🇨🇳 Peking University
GraphEC
🇨🇳 Sun Yat-sen University
ProtENN2
🇺🇸 European Bioinformatics Institute
Qwen2-VL-2B
🇨🇳 Qwen
Qwen2-VL-72B
🇨🇳 Qwen
Qwen2-VL-7B
🇨🇳 Qwen
Qwen2.5-Coder (1.5B)
🇨🇳 Qwen
Qwen2.5-Coder (7B)
🇨🇳 Qwen
RoseTTAFold2-Lite
🇺🇸 University of Washington
AminoAcid-0
🇺🇸 Ginkgo Bioworks
DeepRelax
🇨🇳 National University of Singapore
Mistral Small v24.09
🇫🇷 Mistral AI
OmniGen
🇨🇳 Beijing Academy of Artificial Intelligence / BAAI
ProTeM
🇨🇳 Zhejiang Lab
Qwen2.5-32B
🇨🇳 Qwen
DeepUrfold
🇺🇸 University of Virginia
Playground v3
🇺🇸 Playground
RNA language models predict mutations that improve RNA function
🇺🇸 "NERSC
RNAdiffusion
🇺🇸 Princeton University
UdanDTI
🇨🇳 Tsinghua University
LEGO
🇨🇳 Chinese Academy of Sciences
MolSnapper
🇺🇸 University of Oxford
NeoaPred
🇨🇳 South China University of Technology
PLTNUM
🇯🇵 Kyoto University
ProtRNA
🇨🇳 Fudan University
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.