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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.
Kosmos-2
🇺🇸 Microsoft
RWKV-4 World (7B)
🇺🇸 RWKV Foundation
Inflection-1
🇺🇸 Inflection AI
MPT-30B
🇺🇸 MosaicML
Vicuna-13B-v1.3
🇺🇸 Large Model Systems Organization
Vicuna-33B-v1.3
🇺🇸 Large Model Systems Organization
Vicuna-7B-v1.3
🇺🇸 Large Model Systems Organization
GigaGAN
🇺🇸 POSTECH
WizardCoder-15.5B
🇺🇸 Microsoft
SYNTERACT
🇺🇸 University of Delaware
LTM-1
🇺🇸 Magic
RedPajama-INCITE-7B-Base
🇺🇸 Together
Polyglot-Ko-12.8B
🇺🇸 EleutherAI
TransAct
DPO on Pythia-2.8B
🇺🇸 Stanford University
bpRNA-align
🇺🇸 Oregon State University
BiomedGPT (182M)
🇺🇸 Lehigh University
Guanaco-65B
🇺🇸 University of Washington
RWKV-4 14B
🇺🇸 RWKV Foundation
CodeT5+
🇺🇸 Salesforce
LIMA
🇺🇸 Meta AI
CoEdiT-xxl
🇺🇸 University of Minnesota
Med-PaLM 2
🇺🇸 Google Research
ESM-GearNet
🇺🇸 Mila - Quebec AI (originally Montreal Institute for Learning Algorithms)
PaLM 2
PaLM-2 Bison
PaLM-2 Gecko
PaLM-2 Otter
PaLM-2 Unicorn
MPT-7B
🇺🇸 MosaicML
CodeGen2
🇺🇸 Salesforce
Perfusion
🇺🇸 NVIDIA
OpenLLaMA-13B
🇺🇸 OpenLM Research
MosaicML Diffusion
🇺🇸 Databricks
WizardLM 70B
🇺🇸 Microsoft
WizardLM-7B
🇺🇸 Microsoft
Claude 1.3
🇺🇸 Anthropic
Anthropic LM 52B
🇺🇸 Anthropic
Dolly 2.0-12b
🇺🇸 Databricks
Incoder-6.7B
🇺🇸 Facebook AI Research
DiffDock-PP
🇺🇸 Technical University of Munich
gLM
🇺🇸 Harvard University
Cerebras-GPT-13B
🇺🇸 Cerebras Systems
EigenFold
🇺🇸 Massachusetts Institute of Technology (MIT)
MahLool
🇺🇸 University of Rochester
Pythia-1.4b
🇺🇸 EleutherAI
Pythia-12b
🇺🇸 EleutherAI
Pythia-160m
🇺🇸 EleutherAI
Pythia-1b
🇺🇸 EleutherAI
Pythia-2.8b
🇺🇸 EleutherAI
Pythia-410m
🇺🇸 EleutherAI
Pythia-6.9b
🇺🇸 EleutherAI
Pythia-70m
🇺🇸 EleutherAI
STEPS
🇺🇸 McGill University
BloombergGPT
🇺🇸 Bloomberg
Vicuna-13B v0
🇺🇸 Large Model Systems Organization
Vicuna-7B v0
🇺🇸 Large Model Systems Organization
minChatGPT
🇺🇸 Stanford University
Firefly
🇺🇸 Adobe
Sparse Wide GPT-3 Small
🇺🇸 Cerebras Systems
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.