.. _models_llm_kat-v1: ======================================== KAT-V1 ======================================== - **Context Length:** 131072 - **Model Name:** KAT-V1 - **Languages:** en, zh - **Abilities:** chat - **Description:** Kwaipilot-AutoThink ranks first among all open-source models on LiveCodeBench Pro, a challenging benchmark explicitly designed to prevent data leakage, and even surpasses strong proprietary systems such as Seed and o3-mini. Specifications ^^^^^^^^^^^^^^ Model Spec 1 (pytorch, 40 Billion) ++++++++++++++++++++++++++++++++++++++++ - **Model Format:** pytorch - **Model Size (in billions):** 40 - **Quantizations:** none - **Engines**: vLLM, Transformers, SGLang - **Model ID:** Kwaipilot/KAT-V1-40B - **Model Hubs**: `Hugging Face `__, `ModelScope `__ Execute the following command to launch the model, remember to replace ``${quantization}`` with your chosen quantization method from the options listed above:: xinference launch --model-engine ${engine} --model-name KAT-V1 --size-in-billions 40 --model-format pytorch --quantization ${quantization} Model Spec 2 (gptq, 40 Billion) ++++++++++++++++++++++++++++++++++++++++ - **Model Format:** gptq - **Model Size (in billions):** 40 - **Quantizations:** Int4-Int8Mix - **Engines**: vLLM, Transformers, SGLang - **Model ID:** QuantTrio/KAT-V1-40B-GPTQ-Int4-Int8Mix - **Model Hubs**: `Hugging Face `__, `ModelScope `__ Execute the following command to launch the model, remember to replace ``${quantization}`` with your chosen quantization method from the options listed above:: xinference launch --model-engine ${engine} --model-name KAT-V1 --size-in-billions 40 --model-format gptq --quantization ${quantization} Model Spec 3 (awq, 40 Billion) ++++++++++++++++++++++++++++++++++++++++ - **Model Format:** awq - **Model Size (in billions):** 40 - **Quantizations:** Int4 - **Engines**: vLLM, Transformers, SGLang - **Model ID:** QuantTrio/KAT-V1-40B-AWQ - **Model Hubs**: `Hugging Face `__, `ModelScope `__ Execute the following command to launch the model, remember to replace ``${quantization}`` with your chosen quantization method from the options listed above:: xinference launch --model-engine ${engine} --model-name KAT-V1 --size-in-billions 40 --model-format awq --quantization ${quantization}