benchmark-models

# benchmark-models Run standardized compliance QRA tests against candidate LLMs to evaluate accuracy, latency, and cost before deploying to the inference pipeline. ## Usage ### Run a single-model benchmark ```bash ./run.sh run --model deepseek-v3 --suite compliance-basic ``` Runs 20 gold-set compliance QRA questions against the specified model via `/scillm`. Outputs a results table with TEST_CASE, EXPECTED, ACTUAL, MATCH, and LATENCY_MS columns, plus summary metrics (accuracy%, latency_p50, latency_p95, estimated_token_cost). ### Compare multiple models ```bash ./run.sh compare --models "deepseek-v3,llama-3.1-70b" --suite compliance-basic ``` Runs the benchmark for each model and outputs a side-by-side comparison table. ### View last report ```bash ./run.sh report ``` Reads the most recent benchmark results from `~/.embry/benchmark_results.json` and renders a summary. ### Dry run (no LLM calls) ```bash ./run.sh run --model deepseek-v3 --suite compliance-basic --dry-run ./run.sh compare --models "deepseek-v3,llama-3.1-70b" --dry-run ``` Outputs the full benchmark scaffold with 20 test cases and mock results. No LLM calls are made. ## Suites - **compliance-basic**: 20 gold-set QRA questions covering NIST 800-171, AS9100D, CMMC, ITAR, DFARS, DO-178C, MIL-STD, and cross-program compliance drift detection. ## Output Results are saved to `~/.embry/benchmark_results.json` and printed to stdout. The report includes per-question accuracy and aggregate metrics for model selection decisions.