Model reference · open weights
Kimi-Dev is an open-weight language model from moonshotai. AxForge deploys and operates it for you on dedicated EU-owned hardware — with the licence handled where one is required.
Available as managed deployment — configured and operated for you on dedicated EU hardware, quoted per deployment.
What it is
| Maker | moonshotai |
|---|---|
| Type | Language models |
| Task | Text gen |
| Parameters (lead) | 72.7B |
| Context | 128k tokens |
| Runs with | transformers |
| Based on | Qwen/Qwen2.5-72B |
| Released | 2025-06-16 |
| Popularity | 1k downloads / month |
| Licence | Open weights |
About
Introducing Kimi-Dev: A Strong and Open-source Coding LLM for Issue Resolution
We introduce Kimi-Dev-72B, our new open-source coding LLM for software engineering tasks. Kimi-Dev-72B achieves a new state-of-the-art on SWE-bench Verified among open-source models.
Kimi-Dev-72B achieves 60.4% performance on SWE-bench Verified. It surpasses the runner-up, setting a new state-of-the-art result among open-source models.
Kimi-Dev-72B is optimized via large-scale reinforcement learning. It autonomously patches real repositories in Docker and gains rewards only when the entire test suite passes. This ensures correct and robust solutions, aligning with real-world development standards.
Kimi-Dev-72B is available for download and deployment on Hugging Face and GitHub. We welcome developers and researchers to explore its capabilities and contribute to development.
from transformers import AutoModelForCausalLM, AutoTokenizer
model_name = "moonshotai/Kimi-Dev-72B"
model = AutoModelForCausalLM.from_pretrained(
model_name,
torch_dtype="auto",
device_map="auto"
)
tokenizer = AutoTokenizer.from_pretrained(model_name)
prompt = "Give me a short introduction to large language model."
messages = [
{"role": "system", "content": "You are a helpful assistant."},
{"role": "user", "content": prompt}
]
text = tokenizer.apply_chat_template(
messages,
tokenize=False,
add_generation_prompt=True
)
model_inputs = tokenizer([text], return_tensors="pt").to(model.device)
generated_ids = model.generate(
**model_inputs,
max_new_tokens=512
)
generated_ids = [
output_ids[len(input_ids):] for input_ids, output_ids in zip(model_inputs.input_ids, generated_ids)
]
response = tokenizer.batch_decode(generated_ids, skip_special_tokens=True)[0]
@misc{kimi_dev_72b_2025,
title = {Introducing Kimi-Dev: A Strong and Open-source Coding LLM for Issue Resolution},
author = {{Kimi-Dev Team}},
year = {2025},
month = {June},
url = {\url{https://www.moonshot.cn/Kimi-Dev}}
}
From the published model card. Full card on the HuggingFace links in the sidebar.
Using it via the API
Once AxForge deploys kimi-dev for you, it answers on the OpenAI-compatible API — the same base URL and keys as every other model. (kimi-dev below is illustrative; you get the exact model name on deployment.)
$ curl -sS https://api.axforge.ai/v1/chat/completions \
-H "Authorization: Bearer $AXFORGE_API_KEY" \
-H "Content-Type: application/json" \
-d '{"model":"kimi-dev","messages":[{"role":"user","content":"Hello"}]}'
Create an account — your API key is available in the console. 5M tokens/month currently included with every new account at launch.