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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.
Llama-3.1-Minitron-4B
🇺🇸 NVIDIA
Minitron 4B
🇺🇸 NVIDIA
Minitron 8B
🇺🇸 NVIDIA
KwooLa
🇨🇳 Harbin Institute of Technology
FvFold
🇰🇷 Jeonbuk National University
Lara V1
🇮🇹 Translated
Minerva 7B
🇮🇹 Sapienza NLP
SimPO
🇺🇸 Princeton University
AstroOne
🇨🇳 Zhijiang Lab
Recraft V3
🇬🇧 Recraft
aiXcoder-7B Base
🇨🇳 Peking University
Haiper 2.0
🇬🇧 Haiper
Stable Diffusion 3.5 Medium
🇺🇸 Stability AI
Doubao-pro
🇨🇳 ByteDance
Pro-PRIME
🇺🇸 Shanghai Jiao Tong University
Aya Expanse 32B
🇨🇦 Cohere for AI
Aya Expanse 8B
🇨🇦 Cohere for AI
Bielik 7B
🇵🇱 SpeakLeash
GigaChat MAX
🇷🇺 Sber
YandexGPT 4 Lite
🇷🇺 Yandex
YandexGPT 4 Pro
🇷🇺 Yandex
Claude 3.5 Haiku
🇺🇸 Anthropic
Stable Diffusion 3.5 Large
🇺🇸 Stability AI
Stable Diffusion 3.5 Large Turbo
🇺🇸 Stability AI
Granite 3.0 2B
🇺🇸 IBM
Granite 3.0 8B
🇺🇸 IBM
Depth Anything V2 Giant
🇨🇳 Tik Tok
Depth Anything V2 Large
🇨🇳 Tik Tok
TeleChat2-35B
🇨🇳 China Telecom
Yi-Lightning
🇨🇳 01.AI
Janus 1.3B
🇨🇳 DeepSeek
Marco-o1
🇨🇳 Alibaba
Ministral 3B
🇫🇷 Mistral AI
Ministral 8B
🇫🇷 Mistral AI
CHAI-1
🇺🇸 Chai discovery
Tiangong SkyPaint
🇨🇳 Kunlun Inc.
Alibaba-NLP (mGTE)
🇨🇳 Alibaba
SANA 1.6B
🇺🇸 NVIDIA
MolPath
🇨🇳 Southwest Petroleum University
RNADiffFold
🇨🇳 Hangzhou Institute of Medicine
EvoBind2
🇸🇪 Stockholm University
PROPERMAB
🇺🇸 Regeneron
Yuel 2
🇺🇸 Pennsylvania State University
vScreenML 2.0
🇺🇸 Fox Chase Cancer Center
ALICE
🇨🇳 Nanhu Brain-Computer Interface Institute
Baichuan-Omni
🇨🇳 Baichuan
Deep Learning Enabled Discovery of Kinase Drug Targets in Pharos
🇺🇸 West Virginia University
HaloClass
🇺🇸 University of California Davis
IEV2MOL
🇯🇵 Tokyo Institute of Technology
ProteinChat
🇺🇸 University of California San Diego
AF_unmasked
🇫🇷 Linköping University
ProCALM (Uniref9B)
🇺🇸 Profluent Bio
SCUBA-D
🇨🇳 University of Science and Technology of China (USTC)
CLEAN-Contact
🇺🇸 Cleveland Clinic
Genesis
🇨🇭 Ecole Polytechnique F´ed´erale de Lausanne (EPFL)
SO3LR
🇬🇧 University of Luxembourg
MLDD3UTRmRRNAS
🇺🇸 Ginkgo Bioworks
scHyena
🇰🇷 Korea Advanced Institute of Science and Technology (KAIST)
BindCraft
🇨🇭 Ecole Polytechnique F´ed´erale de Lausanne (EPFL)
EnzymeFlow
🇺🇸 McGill 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.