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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.
Kimi K2
๐จ๐ณ Moonshot
dots.llm1
๐จ๐ณ Rednote
ERNIE-4.5-0.3B
๐จ๐ณ Baidu
ERNIE-4.5-21B-A3B
๐จ๐ณ Baidu
ERNIE-4.5-300B-A47B
๐จ๐ณ Baidu
Hunyuan-A13B (open-source)
๐จ๐ณ Tencent
DiLoCoX (Qwen1.5-107B on WT-103)
๐จ๐ณ Qwen
Kimi Dev 72b
๐จ๐ณ Moonshot
MiniMax-M1-40k
๐จ๐ณ MiniMax
MiniMax-M1-80k
๐จ๐ณ MiniMax
MiniCPM-4-8B
๐จ๐ณ OpenBMB (Open Lab for Big Model Base)
Hunyuan Translation Lite
๐จ๐ณ Tencent
MiMo-7B-Base
๐จ๐ณ Xiaomi Corp
Qwen3 Embedding
๐จ๐ณ Qwen
Qwen3 Reranker
๐จ๐ณ Qwen
Skywork-OR1-32B
๐จ๐ณ Kunlun Inc.
DeepSeek-R1 (May 2025)
๐จ๐ณ DeepSeek
DeepSeek-R1-0528
๐จ๐ณ DeepSeek
Pangu Pro MoE
๐จ๐ณ Huawei
NTele-R1-32B-V1
๐จ๐ณ ZTE
Tianxi-32B
๐จ๐ณ Lenovo
Tianxi-72B
๐จ๐ณ Lenovo
Pangu Ultra MoE
๐จ๐ณ Huawei
DeepSeek-Prover-V2-671B
๐จ๐ณ DeepSeek
DeepSeek-Prover-V2-7B
๐จ๐ณ DeepSeek
Qwen3-0.6B
๐จ๐ณ Qwen
Qwen3-1.7B
๐จ๐ณ Qwen
Qwen3-14B
๐จ๐ณ Qwen
Qwen3-235B-A22B
๐จ๐ณ Qwen
Qwen3-30B-A3B
๐จ๐ณ Qwen
Qwen3-32B
๐จ๐ณ Qwen
Qwen3-4B
๐จ๐ณ Qwen
Qwen3-8B
๐จ๐ณ Qwen
Qwen3 (series)
๐จ๐ณ Alibaba
HiDream-I1
๐จ๐ณ HiDream
UI-TARS-1.5
๐จ๐ณ ByteDance
Seedream 3.0
๐จ๐ณ ByteDance
Kolors 2.0 Image Generation
๐จ๐ณ Kuaishou Technology
360Zhinao3-7B-O1.5
๐จ๐ณ 360 Security Technology
GLM-4-32B-0414
๐จ๐ณ Zhipu AI
GLM-4-9B-0414
๐จ๐ณ Tsinghua University
GLM-Z1-Rumination-32B-0414
๐จ๐ณ Tsinghua University
Pangu Ultra
๐จ๐ณ Huawei
QWQ-Plus
๐จ๐ณ Qwen
Lingju Lingnao
๐จ๐ณ Guangzhou Lingju Information Technology Co Ltd.
QVQ-Max
๐จ๐ณ Alibaba
Lumina-Image-2.0
๐จ๐ณ Shanghai AI Lab
DeepSeek-V3-0324
๐จ๐ณ DeepSeek
Hunyuan TurboS LongText 128K (20250325)
๐จ๐ณ Tencent
Gezhi (ๆ ผ่ดๅคงๆจกๅ)
๐จ๐ณ "Troy Information Technology Co.
ERNIE x1 (ๆๅฟๅคงๆจกๅX1)
๐จ๐ณ Baidu
Meissonic
๐จ๐ณ National University of Singapore
Hunyuan-TurboS
๐จ๐ณ Tencent
Ling-Plus ("Bailing")
๐จ๐ณ Ant Group
Ling-lite-1.5 ("Bailing")
๐จ๐ณ Ant Group
Seedream 2.0
๐จ๐ณ ByteDance
QwQ-32B
๐จ๐ณ Qwen
Spark-X1
๐จ๐ณ iFlytek
Image-01
๐จ๐ณ MiniMax
Kimi 1.6
๐จ๐ณ Moonshot
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.