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[Image blocked: k2-think-banner]K2 Think V2 is a 70 billion parameter open-weights general reasoning model with strong performance in competitive mathematical problem solving built on-top of K2-V2-Instruct, comprising a fully sovereign reasoning model.
We use the following serving configurations:
The provided chat template sets the reasoning effort to high
To serve on VLLM:
You can use K2 Think V2 with Transformers. If you use transformers.pipeline, it will apply the chat template automatically. If you use model.generate directly, you need to apply the chat template mannually.
The chat template is directly inherited from K2-V2-Instruct, with the default reasoning_effort set to "high". The other levels of reasoning effort ("low" and "medium") are still available but have not been tested or evaluated. As such, the model's behavior under such settings is not assured to maintain reported performance.
If you cannot use tokenizer.apply_chat_template, you may also pass in these arguments using extra_body and chat_template_kwargs:
A more complete summary of evaluation results are reported in our Blog
Aggregated across four safety dimensions (Safety-4):
K2 Think V2 establishes a robust safety baseline while effectively resolving the "alignment tax" of previous K2 Think releases. Despite strong overall safety performance, there are still opportunities to improve the model with regard to handling sensitive personal information.
We have employed various techniques to reduce bias, harmful outputs, and other risks in the model. While these efforts help improve safety and reliability, the model, like all Large Language Models, may still generate inaccurate, misleading, biased, or otherwise undesirable content. By downloading, using, or interacting with this model, you acknowledge these limitations and agree to the following:
Prohibited Uses
User Responsibility
No Warranty
If you use K2 Think V2 in your research, please use the following citation:
vllm serve LLM360/K2-Think-V2 --tensor-parallel-size 8 --port 8000from transformers import pipelineimport torch
model_id = "LLM360/K2-Think-V2"
pipe = pipeline( "text-generation", model=model_id, torch_dtype="auto", device_map="auto",)
messages = [ {"role": "user", "content": "what is the next prime number after 2600?"},]
outputs = pipe( messages, max_new_tokens=131072,)print(outputs[0]["generated_text"][-1])from openai import OpenAI
client = OpenAI( base_url="http://localhost:8000/v1", api_key="key")
completion = client.chat.completions.create( model="LLM360/K2-Think-V2", messages = [ {"role": "system", "content": "You are K2-Think, a helpful assistant created by Mohamed bin Zayed University of Artificial Intelligence (MBZUAI) Institute of Foundation Models (IFM)."}, {"role": "user", "content": "Solve the 24 game [2, 3, 5, 6]"} ], extra_body={ "chat_template_kwargs": {"reasoning_effort": "high"}, },)@misc{k2think2026k2think0126, title={K2 {T}hink {V}2: A {F}ully-{S}overeign {R}easoning {M}odel}, author={K2 Think Team and Taylor W. Killian and Varad Pimpalkhute and Richard Fan and Haonan Li and Chengqian Gao and Ming Shan Hee and Xudong Han and John Maggs and Guowei He and Zhengzhong Liu and Eric P. Xing}, year={2026}, url={https://mbzuai.ac.ae/news/k2-think-v2-a-fully-sovereign-reasoning-model}, }