Which AI models can help with GMP work?
GMP Bench is a practical leaderboard for large language models in a pharmaceutical quality, manufacturing, and compliance setting.
AI can meaningfully speed up GMP documentation, but using the right model matters. GMP Bench tests models on real pharmaceutical tasks so teams can make an informed choice: which (local) model actually handles real GMP work, and is it good enough to replace a state of the art cloud model for when you are dealing with sensitive data?
What GMP Bench helps you decide
A model can sound impressive in a chat window and still struggle with regulated pharmaceutical work. GMP Bench looks at the questions quality teams actually need answered.
GMP work creates a lot of critical documentation
In pharmaceutical manufacturing, documentation is not admin overhead. Batch records, SOPs, deviations, CAPAs, validation summaries, environmental monitoring reports, and training records are part of how product quality and patient safety are protected.
AI can speed up document work
Many GMP documents can be drafted faster when a quality or manufacturing expert uses AI as a drafting partner, reviewer, or checklist assistant.
GMP data is often sensitive
Teams may handle patient information, manufacturing know-how, supplier details, investigations, and intellectual property. That makes data control more important than in many other AI use cases.
Local models need a fair comparison
Open-weights models can run entirely inside a company's own infrastructure, no data leaves. GMP Bench shows how they stack up against the best cloud models so teams can make an informed choice.
Top open-weight models
The highest scoring open-weight models across the benchmark.
What we test
The test cases are designed around the two things a pharma user usually needs from AI: correct GMP understanding and useful draft output.
How it works
Submit a test case
Propose a GMP question or document task with a reference answer or scoring rubric.
Models are evaluated
Each model runs the test case. Knowledge answers are checked against references. Document tasks are scored with a rubric.
Compare results
Use the leaderboard to compare model scores by category, provider, or local versus hosted deployment.