Instructions to use moonshotai/Kimi-Linear-48B-A3B-Instruct with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use moonshotai/Kimi-Linear-48B-A3B-Instruct with Transformers:

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

pipe = pipeline("text-generation", model="moonshotai/Kimi-Linear-48B-A3B-Instruct", 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-Linear-48B-A3B-Instruct", trust_remote_code=True, dtype="auto")

Inference
Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use moonshotai/Kimi-Linear-48B-A3B-Instruct with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "moonshotai/Kimi-Linear-48B-A3B-Instruct"
# 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-Linear-48B-A3B-Instruct",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/moonshotai/Kimi-Linear-48B-A3B-Instruct

SGLang

How to use moonshotai/Kimi-Linear-48B-A3B-Instruct 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-Linear-48B-A3B-Instruct" \
    --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-Linear-48B-A3B-Instruct",
		"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-Linear-48B-A3B-Instruct" \
        --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-Linear-48B-A3B-Instruct",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use moonshotai/Kimi-Linear-48B-A3B-Instruct with Docker Model Runner:
```
docker model run hf.co/moonshotai/Kimi-Linear-48B-A3B-Instruct
```

tool parser?

by prudant - opened Nov 1, 2025

Discussion

prudant

Nov 1, 2025

its support function calling with vllm? any config for that?

zhiyuan8

Nov 2, 2025

Kimi Linear is not enhanced by tool calls. However, Kimi Linear can use the same configuration as kimi k2, just specify that the tool parser is kimi_k2.

rekrek

Nov 6, 2025

•

edited Nov 6, 2025

@zhiyuan8 Wish list for next update :

Tool call support
thinking version trained with RL (thinking emulation with system prompt seems to help a bit, so a real thinking model would be great) and kimi-vl-thinking is already partially there
Quantization Aware Training for better 4bit quality with official 4bit variant
coding version with more training on aider/opencode/... and agentic use.
- Honestly, it's a good coder, but (using AWQ 4bit) :
  - it doesn't always follow instructions in aider for diff-edit. Didn't try other coding cli.
  - it fails on generating git diffs sometimes
when issues are fixed, benchmark it on https://aider.chat/docs/leaderboards/. This gets great visibility, like those posts about K2 performances on X or youtube or on r/LocalLLaMA
kimi-cli integration

Frankly it works really well, quite good for local coding. Can't run K2 locally, but this is great.

K2 for architecture planning/debuging large codebase and Kimi-Linear as small coder = best combo !

Kimi-Linear is not available on API ? You should add it, it would be a great addition.

exaple of errors I get in aider :

...
> Use `./TODO.md` file. NOT `engine/TODO.md`
----------------------------------------------------------------------------------------
I'll update the TODO.md file with the changes you specified:

engine/TODO.md
...

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