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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 โ GPT, Claude, Gemini, Llama, Mistral, Qwen and 400+ more โ with parameter counts, context windows, benchmark scores and provider pricing.
CHIEF
๐บ๐ธ Harvard Medical School
MolMVC
๐จ๐ณ Central South University
ChatMol
๐จ๐ณ Tsinghua University
NV-Embed-v2
๐บ๐ธ NVIDIA
Pharia-1-LLM-7B
๐ฉ๐ช Aleph Alpha
Rethinking Molecular Design: Integrating Latent Variable and Auto-Regressive Models for Goal Directed Generation
๐จ๐ญ ETH Zurich
CLR_ESP
๐บ๐ธ Kansas State University
PepMLM
๐บ๐ธ Duke University
EXAONE 3.0
๐ฐ๐ท LG AI Research
Flux.1 [dev]
๐ฉ๐ช Black Forest Labs
Mistral Large 2
๐ซ๐ท Mistral AI
Palmyra Med
๐บ๐ธ Writer
PepPrCLIP
๐บ๐ธ Duke University
Athene-70B
๐บ๐ธ Nexusflow
Modello Italia 9B
๐ฎ๐น iGenius
Igea 3B
๐ฎ๐น University of Pavia
Qwen2 1.5B ITA
๐ฎ๐น DeepMount00
ESM3-open-small
๐บ๐ธ EvolutionaryScale
GLM-4V-9B
๐จ๐ณ Zhipu AI
FoldFlow2
๐ฌ๐ง Dreamfold
Codestral
๐ซ๐ท Mistral AI
NV-Embed-v1
๐บ๐ธ NVIDIA
BRIA 2.3
๐บ๐ธ BRIA AI
AlphaFold 3
๐บ๐ธ Google DeepMind
OpenELM-1.1B
๐บ๐ธ Apple
OpenELM-270M
๐บ๐ธ Apple
OpenELM-3B
๐บ๐ธ Apple
OpenELM-450M
๐บ๐ธ Apple
DanteLLM 7B
๐ฎ๐น RSTLess Research
GenCast
๐บ๐ธ Google DeepMind
LLaMAntino-3 ANITA 8B
๐ฎ๐น University of Bari
Llama-3 8B ITA
๐ฎ๐น DeepMount00
Multi-Token Prediction 7B
๐บ๐ธ Facebook AI Research
Command R+
๐จ๐ฆ Cohere
XVERSE-MoE-A4.2B
๐จ๐ณ XVERSE Technology
Volare
๐ฎ๐น Moxoff
Command R
๐จ๐ฆ Cohere
Azzurro
๐ฎ๐น Moxoff
Maestrale Chat v0.4
๐ฎ๐น mii-llm
Mistral ITA 7B
๐ฎ๐น DeepMount00
PTM-Mamba
๐บ๐ธ Duke University
Me Llama 13B
๐บ๐ธ Yale School of Medicine
Me Llama 70B
๐บ๐ธ Yale School of Medicine
Stable Cascade
๐บ๐ธ Stability AI
Zefiro
๐ฎ๐น mii-llm
StableLM-2-1.6B
๐บ๐ธ Stability AI
Stable Code 3B
๐บ๐ธ Stability AI
Baize-v2-13B (็ฝๆณฝ)
๐บ๐ธ University of California San Diego
LLaMAntino-2
๐ฎ๐น University of Bari
SD-Turbo
๐บ๐ธ Stability AI
Starling-LM-7B-alpha
๐บ๐ธ University of California (UC) Berkeley
Orca 2-13B
๐บ๐ธ Microsoft Research
Mistral 7B + OVM
๐บ๐ธ Chinese University of Hong Kong (CUHK)
Mi:dm 7B
๐ฐ๐ท KT
GraphCast
๐บ๐ธ Google DeepMind
Volcano 13B
๐บ๐ธ Korea University
LingoWhale-8B
๐จ๐ณ DeepLang AI
Spec-Drafter
๐จ๐ณ Peking University
PULI GPTrio
๐ญ๐บ Hungarian Research Centre for Linguistics
Platypus-70B
๐บ๐ธ Boston University
About Large language models (LLMs)
Large language models (LLMs) are the foundation of modern generative AI โ 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 โ 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 โ 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.