HAVEN combines LLM agents for planning and gap analysis with protocol-specific templates and a custom DSL to generate correct UVM testbenches, achieving 100% compilation success, 90.6% code coverage, and 87.9% functional coverage on 19 open-source designs across three protocols.
RealBench: Benchmarking Verilog Generation Models with Real-World IP Designs
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InCoder-32B-Thinking uses error-feedback synthesized thinking traces and a code world model to reach top open-source scores on general and industrial code benchmarks including 81.3% on LiveCodeBench and 84.0% on CAD-Coder.
Agentic Agile-V uses Agile-V as backbone and a Specify-Constrain-Orchestrate-Prove-Evolve-Verify loop to convert AI agent conversations into traceable engineering artifacts with acceptance evidence.
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InCoder-32B-Thinking: Industrial Code World Model for Thinking
InCoder-32B-Thinking uses error-feedback synthesized thinking traces and a code world model to reach top open-source scores on general and industrial code benchmarks including 81.3% on LiveCodeBench and 84.0% on CAD-Coder.