LLM Models
Browse the world's large language models. Compare parameters, benchmarks, VRAM and more.
Qwen2.5 is the latest series of Qwen large language models. For Qwen2.5, we release a number of base language models and instruction-tuned language models ranging from 0.5 to 72 billion parameters. Qwen2.5 brings the following improvements upon Qwen2:
:--- :--- Total Parameters 550B (55B active) Architecture LatentMoE - Mamba-2 + MoE + Attention hybrid with Multi-Token Prediction (MTP) Context Length Up to 1M tokens Minimum GPU Requirement 8x GB200/B200/GB300/B300, 16x H100, 8x H200 Supported Languages English, French, Spanish…
:--- :--- Total Parameters 550B (55B active) Architecture LatentMoE - Mamba-2 + MoE + Attention hybrid with Multi-Token Prediction (MTP) Context Length Up to 1M tokens Minimum GPU Requirement 4xGB200, 4xB200, 4x GB300, 4x B300, 8xH100 Supported Languages English, French, Spanish,…
--- --- Developers Granite Team, IBM Model Type Decoder-only Dense Transformer (Reasoning) Architecture GraniteForCausalLM Base Model Granite-4.1-30B-Base Parameters 30B Context Length Natively Supports 128K (Long-context extension to 512K) Precision bfloat16 Tested Languages Eng…
:--- :--- Total Parameters 120B (12B active) Architecture LatentMoE - Mamba-2 + MoE + Attention hybrid with Multi-Token Prediction (MTP) Context Length Up to 1M tokens Minimum GPU Requirement 8× H100-80GB Supported Languages English, French, German, Italian, Japanese, Spanish, Ch…
:--- :--- Total Parameters 120B (12B active) Architecture LatentMoE - Mamba-2 + MoE + Attention hybrid with Multi-Token Prediction (MTP) Context Length Up to 1M tokens Minimum GPU Requirement 1× B200 OR 1× DGX Spark Supported Languages English, French, German, Italian, Japanese,…
:--- :--- Total Parameters 120B (12B active) Architecture LatentMoE - Mamba-2 + MoE + Attention hybrid with Multi-Token Prediction (MTP) Context Length Up to 1M tokens Minimum GPU Requirement 2× H100-80GB Supported Languages English, French, German, Italian, Japanese, Spanish, Ch…
--- --- Developers Granite Team, IBM Model Type Decoder-only Dense Transformer (Reasoning) Architecture GraniteForCausalLM Base Model Granite-4.1-8B-Base Parameters 8B Context Length Natively Supports 128K (Long-context extension to 512K) Precision bfloat16 Tested Languages Engli…
The post-training data has a cutoff date of November 28, 2025\. The pre-training data has a cutoff date of June 25, 2025\.
The post-training data has a cutoff date of November 28, 2025\. The pre-training data has a cutoff date of June 25, 2025\.
