Living Models paired Gemma 4 with BOTANIC-1, a plant genome foundation model, to identify causal mutations in crop breeding. The system solved a decades-old genetics problem—distinguishing which mutation actually drives a trait from dozens of hitchhiking variants—in hours instead of months of field trials.

• Classical bioinformatics tools hit a wall on the melon test case, narrowing 47,492 variants to 3,061 candidates but couldn't break linkage disequilibrium to identify the true causal CmEIN3 mutation; BOTANIC-1 ranked it #1 out of 2,494 SNPs using evolutionary constraint scoring.
• BOTANIC-1 placed true causal mutations in the top 0.1% of candidates in 15.9% of cases across 500+ validated mutations, versus 4.6% for the best non-GLM baseline, and in the top 1% in 48.8% of cases versus 33.9% for classical pipelines.
• The modular architecture runs Gemma 4 E4B locally on a single NVIDIA L4 GPU via Ollama, keeping proprietary genomes on-premises while slashing costs and making domain-specialist AI accessible on standard hardware.