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README.md
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---
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license: mit
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base_model:
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- moonshotai/Kimi-Dev-72B
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tags:
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- code
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- unsloth
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- swebench
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- software
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- issue-resolving
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---
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<div>
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<p style="margin-top: 0;margin-bottom: 0;">
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<em><a href="https://docs.unsloth.ai/basics/unsloth-dynamic-v2.0-gguf">Unsloth Dynamic 2.0</a> achieves superior accuracy & outperforms other leading quants.</em>
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</p>
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<div style="display: flex; gap: 5px; align-items: center; ">
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<a href="https://github.com/unslothai/unsloth/">
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<img src="https://github.com/unslothai/unsloth/raw/main/images/unsloth%20new%20logo.png" width="133">
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</a>
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<a href="https://discord.gg/unsloth">
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<img src="https://github.com/unslothai/unsloth/raw/main/images/Discord%20button.png" width="173">
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</a>
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<a href="https://docs.unsloth.ai/basics/qwen3-how-to-run-and-fine-tune">
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<img src="https://raw.githubusercontent.com/unslothai/unsloth/refs/heads/main/images/documentation%20green%20button.png" width="143">
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</a>
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</div>
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</div>
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<!-- # Kimi-Dev -->
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<div align="center">
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<img src="./assets/main_logo.png" alt="Kimi Logo" width="400" />
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<h2><a href="https://moonshotai.github.io/Kimi-Dev/">
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Introducing Kimi-Dev: <br>A Strong and Open-source Coding LLM for Issue Resolution</a></h2>
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</a></h2>
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<b>Kimi-Dev Team</b>
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<br>
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</div>
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<div align="center">
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<a href="">
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<b>📄 Tech Report (Coming soon...)</b>
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</a> |
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<a href="https://github.com/MoonshotAI/Kimi-Dev">
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<b>📄 Github</b>
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</a>
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</div>
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<br>
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<br>
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<!-- https://github.com/MoonshotAI/Kimi-Dev -->
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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.
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- 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.
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- 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.
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- 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.
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<div align="center">
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<img src="./assets/open_performance_white.png" alt="Kimi Logo" width="600" />
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<p><b>Performance of Open-source Models on SWE-bench Verified.</b></p>
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</div>
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## Quick Start
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```
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from transformers import AutoModelForCausalLM, AutoTokenizer
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model_name = "moonshotai/Kimi-Dev-72B"
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model = AutoModelForCausalLM.from_pretrained(
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model_name,
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torch_dtype="auto",
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device_map="auto"
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)
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tokenizer = AutoTokenizer.from_pretrained(model_name)
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prompt = "Give me a short introduction to large language model."
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messages = [
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{"role": "system", "content": "You are a helpful assistant."},
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{"role": "user", "content": prompt}
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]
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text = tokenizer.apply_chat_template(
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messages,
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tokenize=False,
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add_generation_prompt=True
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)
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model_inputs = tokenizer([text], return_tensors="pt").to(model.device)
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generated_ids = model.generate(
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**model_inputs,
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max_new_tokens=512
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)
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generated_ids = [
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output_ids[len(input_ids):] for input_ids, output_ids in zip(model_inputs.input_ids, generated_ids)
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]
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response = tokenizer.batch_decode(generated_ids, skip_special_tokens=True)[0]
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```
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## Citation
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```
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@misc{kimi_dev_72b_2025,
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title = {Introducing Kimi-Dev: A Strong and Open-source Coding LLM for Issue Resolution},
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author = {{Kimi-Dev Team}},
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year = {2025},
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month = {June},
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url = {\url{https://www.moonshot.cn/Kimi-Dev}}
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}
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```
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