README.md

metadata

base_model: Qwen/Qwen3.5-9B
license: apache-2.0
pipeline_tag: text-generation
tags:
  - rtl
  - verilog
  - multi-agent
  - code-generation

ChipMATE-P-9B

• Website: https://chipmate.picasso-lab.com
• GitHub: https://github.com/zhongkaiyu/ChipMATE
• Paper: ChipMATE: Multi-Agent Training via Reinforcement Learning for Enhanced RTL Generation

This is the Python reference-model generation agent of ChipMATE, released as the final checkpoint after the multi-agent reinforcement-learning stage described in the paper.

ChipMATE is a self-trained multi-agent framework for RTL generation that pairs a Verilog agent with a Python reference-model agent. The two agents cross-verify each other's outputs to produce high-quality RTL code without relying on any golden testbench -- matching the way correctness is established in real industrial chip-design flows.

Model details

• Track: Python reference-model generation
• Backbone: Qwen3.5-9B
• Training stage: Stage 2 (multi-agent RL) -- final checkpoint
• Companion agent: core12345/ChipMATE-V-9B

Usage

To use this model as part of the ChipMATE framework, you can serve it using vLLM as an OpenAI-compatible endpoint:

# Serve the Python reference-model agent
vllm serve core12345/ChipMATE-P-9B --port 8002

Then, you can interface with it using the chipmate library:

from chipmate import make_backend, run_problem

# Note: This agent is designed to work in tandem with a Verilog agent
p_backend = make_backend(model="core12345/ChipMATE-P-9B",
                         base_url="http://localhost:8002/v1", api_key="dummy")

v_backend = make_backend(model="core12345/ChipMATE-V-9B",
                         base_url="http://localhost:8001/v1", api_key="dummy")

result = run_problem(
    task_id="my_problem",
    question="Implement a Verilog module that ...",
    ref_sv="module top_module(input clk, ...);
endmodule
",
    v_backend=v_backend,
    p_backend=p_backend,
)
print(result.verilog)             # final Verilog implementation

The ChipMATE model series

	Verilog agent	Python ref-model agent
4B	core12345/ChipMATE-V-4B	core12345/ChipMATE-P-4B
9B	core12345/ChipMATE-V-9B	core12345/ChipMATE-P-9B

Citation

@article{yu2025chipmate,
  title={ChipMATE: Multi-Agent Training via Reinforcement Learning for Enhanced RTL Generation},
  author={Yu, Zhongkai and Lin, Yichen and others},
  journal={arXiv preprint arXiv:2605.12857},
  year={2025}
}