AS-SiliconMind/SiliconMind-V1-Qwen3-4B-T-2507-76k

SiliconMind-V1-Qwen3-4B-T-2507-76k: Verilog Code Generation with Debug-Reasoning

This model is part of the SiliconMind-V1 family, developed by AS-SiliconMind, and is specifically designed for Verilog code generation, testing, and debugging. Fine-tuned from Qwen3-4B-Thinking-2507, this variant utilizes an expanded 76k-sample training mix, focusing on a multi-agent framework for reasoning-oriented data generation and testbench-driven verification.

Key Capabilities

• Reasoning-Oriented: Produces reasoning traces to guide functional correctness before generating code.
• Self-Testing & Debugging: Can generate its own test reports and fix bugs without relying on external tool-calling.
• Tool-Free Verification: Reduces the need for proprietary Electronic Design Automation (EDA) software during the code generation process.
• Multi-Strategy Inference: Supports Regular, Deep Thinking, and Agentic inference modes, allowing trade-offs between latency, cost, and accuracy.

Training and Differentiation

This model was trained using a two-phase pipeline: a Code Generation Phase with a multi-agent system to synthesize 76k functionally verified tuples, and a Self-Correction Phase that augmented hard samples with "Test" and "Debug" curriculum. This approach teaches the model to write test reports and self-correct errors, distinguishing it from models that only generate code. While benchmark results for this 76k variant are pending, it represents an advancement over the original 36k variant.

Good For

• Developers requiring Verilog RTL design generation.
• Use cases benefiting from integrated self-testing and debugging capabilities.
• Projects aiming to reduce reliance on external EDA tools for verification.
• Applications needing iterative code refinement through agentic workflows for highest pass rates.