Instructions to use moonshotai/Kimi-K2-Instruct-0905 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use moonshotai/Kimi-K2-Instruct-0905 with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="moonshotai/Kimi-K2-Instruct-0905", trust_remote_code=True)
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoModelForCausalLM
model = AutoModelForCausalLM.from_pretrained("moonshotai/Kimi-K2-Instruct-0905", trust_remote_code=True, dtype="auto")

Inference
HuggingChat
Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use moonshotai/Kimi-K2-Instruct-0905 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "moonshotai/Kimi-K2-Instruct-0905"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "moonshotai/Kimi-K2-Instruct-0905",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/moonshotai/Kimi-K2-Instruct-0905

SGLang

How to use moonshotai/Kimi-K2-Instruct-0905 with SGLang:

Install from pip and serve model

# Install SGLang from pip:
pip install sglang
# Start the SGLang server:
python3 -m sglang.launch_server \
    --model-path "moonshotai/Kimi-K2-Instruct-0905" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "moonshotai/Kimi-K2-Instruct-0905",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker images

docker run --gpus all \
    --shm-size 32g \
    -p 30000:30000 \
    -v ~/.cache/huggingface:/root/.cache/huggingface \
    --env "HF_TOKEN=<secret>" \
    --ipc=host \
    lmsysorg/sglang:latest \
    python3 -m sglang.launch_server \
        --model-path "moonshotai/Kimi-K2-Instruct-0905" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "moonshotai/Kimi-K2-Instruct-0905",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use moonshotai/Kimi-K2-Instruct-0905 with Docker Model Runner:
```
docker model run hf.co/moonshotai/Kimi-K2-Instruct-0905
```

Unstable tool calling compared with 0711 version

by arnrightnow - opened Sep 5, 2025

Discussion

arnrightnow

Sep 5, 2025

•

edited Sep 5, 2025

Using the exact same prompt including the exact same tool descriptions, kimi-k2-0711 correctly calls the tool but 0905 will return the tool call string <tool_name>Arguments...</tool_name> instead of sending back a tool call reponse with finish_reason of tool_call.

When it works, it works perfectly with high precision tool calling but most of the time it just doesn't call the tools or I would need some weird prompt tweaking to make it work.

Update: Managed to reproduce the issue in a relatively stable manner. I defined a grep like tool which takes a pattern parameter to search for a regex in a piece of text. As long as I have this tool passed to the 0905 model, it just stops working. But the 0711 model handles the tool and calls the tool correctly.

jerryzhuang

Sep 8, 2025

I have the same feeling with you. the tool calling is unstable.

ccocks-deca

Sep 20, 2025

@arnrightnow

This happens because kimi was finetuned for agents which use this format.

Chandra-shekhar-reddy

Sep 24, 2025

will the reason for tool call with 0905 is this : https://huggingface.co/moonshotai/Kimi-K2-Instruct-0905/blob/main/chat_template.jinja#L18?
https://huggingface.co/moonshotai/Kimi-K2-Instruct/blob/main/chat_template.jinja#L18

In 0905 it's been written as {% endif %} where as in 0711 it been written as {%- endif -%}
closure look tells there is '-' missing.

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