LLM Regression Testing Explained
Regression testing catches when model updates introduce bugs or degrade performance. This guide explains how to set up and run regression tests for LLMs.
What Is LLM Regression Testing?
LLM regression testing ensures that model updates don't break existing functionality. You maintain a test suite of inputs and expected outputs, then run these tests after each update to catch:
- Performance degradation (accuracy drops, latency increases)
- Behavior changes (outputs that used to be correct are now wrong)
- New failure modes (hallucinations, safety issues)
- Breaking changes in API or output format
Regression tests run automatically in CI/CD pipelines and before production deployments.
How Do You Set Up Regression Tests for LLMs?
Build your regression test suite by:
- Collecting representative inputs from production or user queries
- Establishing baseline outputs (expected responses) for each input
- Defining evaluation criteria (accuracy, relevance, safety)
- Setting up automated test runners that execute tests on model updates
- Tracking metrics over time to identify trends
Start with critical user paths and high-risk scenarios, then expand coverage over time.
How Do You Handle Non-Deterministic Outputs in Regression Tests?
LLMs produce non-deterministic outputs, so you can't use exact string matching. Instead:
- Use semantic similarity metrics (cosine similarity, embeddings)
- Check for key facts or concepts rather than exact wording
- Evaluate against criteria (relevance, accuracy, safety) rather than exact matches
- Test multiple times and measure consistency ranges
- Set thresholds for acceptable variance
Focus on whether outputs meet quality standards, not whether they match exactly.
When Should You Run Regression Tests?
Run regression tests:
- Before every production deployment
- After model updates or fine-tuning
- After prompt engineering changes
- After infrastructure or API changes
- Continuously in production to catch gradual degradation
Integrate regression tests into your CI/CD pipeline so they run automatically on every code change.
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Frequently Asked Questions
How many regression tests should I have?
Start with 50-100 tests covering critical user paths. Expand to 500-1000+ tests over time as you discover edge cases. Focus on quality over quantity—ensure tests cover high-value, high-risk scenarios.
What if my regression tests fail after a model update?
Investigate whether the failure is a real regression or an expected change. If it's a regression, roll back the update or fix the issue. If it's expected (e.g., improved outputs), update your test baselines.
How do I maintain regression test suites over time?
Review and update test suites quarterly. Remove obsolete tests, add tests for new features, and update baselines when outputs legitimately improve. Keep tests focused on critical paths to avoid maintenance burden.
Can I use the same regression tests for different LLM providers?
Yes, but you'll need different baselines for each provider since outputs vary. Use the same test inputs and evaluation criteria, but maintain separate expected outputs for each model or provider.