GLM-5.3 is live. Run Z.ai's latest model on Friendli Model APIs. Try it today ➜
kcxain
Available on FriendliAI
Run this model inference on single tenant GPU with unmatched speed and reliability at scale.
Model Details
Model Provider
kcxain
Model Tree
Qwen/Qwen2.5-Coder-7B-Instruct
Input Modalities
Output Modalities
Supported Functionality
KernelZero: Continual Co-Evolution of LLMs for Kernel Generation
The paper reports the following results with 10 sampled candidates per problem.
| Benchmark | pass@1 | pass@5 | pass@10 | fast_1@1 | fast_1@10 | fast_2@1 | fast_2@10 |
|---|---|---|---|---|---|---|---|
| Level 1 | 75.8 | 98.87 | 100.0 | 17.6 | 29.0 | 7.2 | 12.0 |
| Level 2 | 69.6 | 93.70 | 97.0 | 2.4 | 12.0 | 1.2 | 6.0 |
This checkpoint generates CUDA extensions from PyTorch modules. Use the same prompt template and validation environment as KernelZero for reproducible evaluation.
python
from transformers import AutoModelForCausalLM, AutoTokenizer model_id = "kcxain/KernelZero-CUDA-7B"tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)model = AutoModelForCausalLM.from_pretrained( model_id, torch_dtype="auto", device_map="auto", trust_remote_code=True,)This release contains the merged Hugging Face inference weights from the final 80-step CUDA Coder followed by the 40-step continuation used for the paper's main CUDA result. Optimizer states and distributed training shards are excluded.