GLM-5.3 is live. Run Z.ai's latest model on Friendli Model APIs. Try it today ➜
skt
Available on FriendliAI
Run this model inference on single tenant GPU with unmatched speed and reliability at scale.
Model Details
Model Provider
skt
Model Tree
Input Modalities
Output Modalities
Supported Functionality
SK Telecom released A.X 4.0 (pronounced "A dot X"), a large language model (LLM) optimized for Korean-language understanding and enterprise deployment, on July 03, 2025. Built on the open-source Qwen2.5 model, A.X 4.0 has been further trained with large-scale Korean datasets to deliver outstanding performance in real-world business environments.
transformers>=4.46.0 or the latest version is required to use skt/A.X-4.0-Lightbash
pip install transformers>=4.46.0python
import torchfrom transformers import AutoModelForCausalLM, AutoTokenizer model_name = "skt/A.X-4.0-Light"model = AutoModelForCausalLM.from_pretrained( model_name, torch_dtype=torch.bfloat16, device_map="auto",)model.eval()tokenizer = AutoTokenizer.from_pretrained(model_name) messages = [ {"role": "system", "content": "당신은 사용자가 제공하는 영어 문장들을 한국어로 번역하는 AI 전문가입니다."}, {"role": "user", "content": "The first human went into space and orbited the Earth on April 12, 1961."},]input_ids = tokenizer.apply_chat_template(messages, add_generation_prompt=True, return_tensors="pt").to(model.device) with torch.no_grad(): output = model.generate( input_ids, max_new_tokens=128, do_sample=False, ) len_input_prompt = len(input_ids[0])response = tokenizer.decode(output[0][len_input_prompt:], skip_special_tokens=True)print(response)# Output:# 1961년 4월 12일, 최초의 인간이 우주로 나가 지구를 공전했습니다.vllm>=v0.6.4.post1 or the latest version is required to use tool-use functionbash
pip install vllm>=v0.6.4.post1# if you don't want to activate tool-use function, just commenting out below vLLM optionVLLM_OPTION="--enable-auto-tool-choice --tool-call-parser hermes"vllm serve skt/A.X-4.0-Light $VLLM_OPTIONpython
from openai import OpenAI def call(messages, model): completion = client.chat.completions.create( model=model, messages=messages, ) print(completion.choices[0].message) client = OpenAI( base_url="http://localhost:8000/v1", api_key="api_key")model = "skt/A.X-4.0-Light"messages = [{"role": "user", "content": "에어컨 여름철 적정 온도는? 한줄로 답변해줘"}]call(messages, model)# Output:# ChatCompletionMessage(content='여름철 적정 에어컨 온도는 일반적으로 24-26도입니다.', refusal=None, role='assistant', audio=None, function_call=None, tool_calls=[], reasoning_content=None) messages = [{"role": "user", "content": "What is the appropriate temperature for air conditioning in summer? Response in a single sentence."}]call(messages, model)# Output:# ChatCompletionMessage(content='The appropriate temperature for air conditioning in summer generally ranges from 72°F to 78°F (22°C to 26°C) for comfort and energy efficiency.', refusal=None, role='assistant', audio=None, function_call=None, tool_calls=[], reasoning_content=None)python
from openai import OpenAI def call(messages, model): completion = client.chat.completions.create( model=model, messages=messages, tools=tools ) print(completion.choices[0].message) client = OpenAI( base_url="http://localhost:8000/v1", api_key="api_key")model = "skt/A.X-4.0-Light" calculate_discount = { "type": "function", "function": { "name": "calculate_discount", "description": "원가격과 할인율(퍼센트 단위)을 입력받아 할인된 가격을계산한다.", "parameters": { "type": "object", "properties": { "original_price": { "type": "number", "description": "상품의 원래 가격" }, "discount_percentage": { "type": "number", "description": "적용할 할인율(예: 20% 할인의 경우 20을 입력)" } }, "required": ["original_price", "discount_percentage"] } }}get_exchange_rate = { "type": "function", "function": { "name": "get_exchange_rate", "description": "두 통화 간의 환율을 가져온다.", "parameters": { "type": "object", "properties": { "base_currency": { "type": "string", "description": "The currency to convert from." }, "target_currency": { "type": "string", "description": "The currency to convert to." } }, "required": ["base_currency", "target_currency"] } }}tools = [calculate_discount, get_exchange_rate] ### Slot filling ###messages = [{"role": "user", "content": "우리가 뭘 사야되는데 원래 57600원인데 직원할인 받을 수 있거든? 할인가좀 계산해줘"}]call(messages, model)# Output:# ChatCompletionMessage(content='할인율을 알려주시겠습니까?', refusal=None, role='assistant', audio=None, function_call=None, tool_calls=[], reasoning_content=None) ### Function calling ###messages = [ {"role": "user", "content": "우리가 뭘 사야되는데 원래 57600원인데 직원할인 받을 수 있거든? 할인가좀 계산해줘"}, {"role": "assistant", "content": "할인율을 알려주시겠습니까?"}, {"role": "user", "content": "15% 할인 받을 수 있어."},]call(messages, model)# Output: # ChatCompletionMessage(content=None, refusal=None, role='assistant', audio=None, function_call=None, tool_calls=[ChatCompletionMessageToolCall(id='chatcmpl-tool-7778d1d9fca94bf2acbb44c79359502c', function=Function(arguments='{"original_price": 57600, "discount_percentage": 15}', name='calculate_discount'), type='function')], reasoning_content=None) ### Completion ###messages = [ {"role": "user", "content": "우리가 뭘 사야되는데 원래 57600원인데 직원할인 받을 수 있거든? 할인가좀 계산해줘"}, {"role": "assistant", "content": "할인율을 알려주시겠습니까?"}, {"role": "user", "content": "15% 할인 받을 수 있어."}, {"role": "tool", "tool_call_id": "random_id", "name": "calculate_discount", "content": "{\"original_price\": 57600, \"discount_percentage\": 15, \"discounted_price\": 48960.0}"}]call(messages, model)# Output: # ChatCompletionMessage(content='57600원의 상품에서 15% 할인을 적용하면, 할인된 가격은 48960원입니다.', refusal=None, role='assistant', audio=None, function_call=None, tool_calls=[], reasoning_content=None)The A.X 4.0 Light model is licensed under Apache License 2.0.
text
@article{SKTAdotX4Light, title={A.X 4.0 Light}, author={SKT AI Model Lab}, year={2025}, url={https://huggingface.co/skt/A.X-4.0-Light}}import torchfrom transformers import AutoModelForCausalLM, AutoTokenizer model_name = "skt/A.X-4.0-Light"model = AutoModelForCausalLM.from_pretrained( model_name, torch_dtype=torch.bfloat16, device_map="auto",)model.eval()tokenizer = AutoTokenizer.from_pretrained(model_name) messages = [ {"role": "system", "content": "당신은 사용자가 제공하는 영어 문장들을 한국어로 번역하는 AI 전문가입니다."}, {"role": "user", "content": "The first human went into space and orbited the Earth on April 12, 1961."},]input_ids = tokenizer.apply_chat_template(messages, add_generation_prompt=True, return_tensors="pt").to(model.device) with torch.no_grad(): output = model.generate( input_ids, max_new_tokens=128, do_sample=False, ) len_input_prompt = len(input_ids[0])response = tokenizer.decode(output[0][len_input_prompt:], skip_special_tokens=True)print(response)# Output:# 1961년 4월 12일, 최초의 인간이 우주로 나가 지구를 공전했습니다.pip install vllm>=v0.6.4.post1# if you don't want to activate tool-use function, just commenting out below vLLM optionVLLM_OPTION="--enable-auto-tool-choice --tool-call-parser hermes"vllm serve skt/A.X-4.0-Light $VLLM_OPTIONfrom openai import OpenAI def call(messages, model): completion = client.chat.completions.create( model=model, messages=messages, ) print(completion.choices[0].message) client = OpenAI( base_url="http://localhost:8000/v1", api_key="api_key")model = "skt/A.X-4.0-Light"messages = [{"role": "user", "content": "에어컨 여름철 적정 온도는? 한줄로 답변해줘"}]call(messages, model)# Output:# ChatCompletionMessage(content='여름철 적정 에어컨 온도는 일반적으로 24-26도입니다.', refusal=None, role='assistant', audio=None, function_call=None, tool_calls=[], reasoning_content=None) messages = [{"role": "user", "content": "What is the appropriate temperature for air conditioning in summer? Response in a single sentence."}]call(messages, model)# Output:# ChatCompletionMessage(content='The appropriate temperature for air conditioning in summer generally ranges from 72°F to 78°F (22°C to 26°C) for comfort and energy efficiency.', refusal=None, role='assistant', audio=None, function_call=None, tool_calls=[], reasoning_content=None)from openai import OpenAI def call(messages, model): completion = client.chat.completions.create( model=model, messages=messages, tools=tools ) print(completion.choices[0].message) client = OpenAI( base_url="http://localhost:8000/v1", api_key="api_key")model = "skt/A.X-4.0-Light" calculate_discount = { "type": "function", "function": { "name": "calculate_discount", "description": "원가격과 할인율(퍼센트 단위)을 입력받아 할인된 가격을계산한다.", "parameters": { "type": "object", "properties": { "original_price": { "type": "number", "description": "상품의 원래 가격" }, "discount_percentage": { "type": "number", "description": "적용할 할인율(예: 20% 할인의 경우 20을 입력)" } }, "required": ["original_price", "discount_percentage"] } }}get_exchange_rate = { "type": "function", "function": { "name": "get_exchange_rate", "description": "두 통화 간의 환율을 가져온다.", "parameters": { "type": "object", "properties": { "base_currency": { "type": "string", "description": "The currency to convert from." }, "target_currency": { "type": "string", "description": "The currency to convert to." } }, "required": ["base_currency", "target_currency"] } }}tools = [calculate_discount, get_exchange_rate] ### Slot filling ###messages = [{"role": "user", "content": "우리가 뭘 사야되는데 원래 57600원인데 직원할인 받을 수 있거든? 할인가좀 계산해줘"}]call(messages, model)# Output:# ChatCompletionMessage(content='할인율을 알려주시겠습니까?', refusal=None, role='assistant', audio=None, function_call=None, tool_calls=[], reasoning_content=None) ### Function calling ###messages = [ {"role": "user", "content": "우리가 뭘 사야되는데 원래 57600원인데 직원할인 받을 수 있거든? 할인가좀 계산해줘"}, {"role": "assistant", "content": "할인율을 알려주시겠습니까?"}, {"role": "user", "content": "15% 할인 받을 수 있어."},]call(messages, model)# Output: # ChatCompletionMessage(content=None, refusal=None, role='assistant', audio=None, function_call=None, tool_calls=[ChatCompletionMessageToolCall(id='chatcmpl-tool-7778d1d9fca94bf2acbb44c79359502c', function=Function(arguments='{"original_price": 57600, "discount_percentage": 15}', name='calculate_discount'), type='function')], reasoning_content=None) ### Completion ###messages = [ {"role": "user", "content": "우리가 뭘 사야되는데 원래 57600원인데 직원할인 받을 수 있거든? 할인가좀 계산해줘"}, {"role": "assistant", "content": "할인율을 알려주시겠습니까?"}, {"role": "user", "content": "15% 할인 받을 수 있어."}, {"role": "tool", "tool_call_id": "random_id", "name": "calculate_discount", "content": "{\"original_price\": 57600, \"discount_percentage\": 15, \"discounted_price\": 48960.0}"}]call(messages, model)# Output: # ChatCompletionMessage(content='57600원의 상품에서 15% 할인을 적용하면, 할인된 가격은 48960원입니다.', refusal=None, role='assistant', audio=None, function_call=None, tool_calls=[], reasoning_content=None)@article{SKTAdotX4Light, title={A.X 4.0 Light}, author={SKT AI Model Lab}, year={2025}, url={https://huggingface.co/skt/A.X-4.0-Light}}