Model trained on DNA of 320 plant species, used with Gemma 4 as a scientist agent to rank candidate mutations. Ranked the correct mutation first among about 2,500 candidates 90% of the time.
Botanic 1
Plant genomic language model from Living Models, trained on 320 plant species and paired with Gemma 4 for crop genetics.
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Botanic 1 at a glance
- What is Botanic 1?
- Botanic 1 is a model from Google DeepMind. Plant genomic language model from Living Models, trained on 320 plant species and paired with Gemma 4 for crop genetics.
- Who makes Botanic 1?
- Botanic 1 is made by Google DeepMind.
- Does Botanic 1 work in the EU?
- Unverified. No explicit evidence found. The developer, Living Models, is Paris-based and collaborates with INRAE, but no public availability terms or regional restrictions are given. Last verified 14 Nov 2026.
- How much does Botanic 1 cost?
- Pricing unknown. No pricing or access terms for BOTANIC-1 given in the provided material.
- Where was Botanic 1 shown?
- In 1 creator video by AI Search. Most recently by AI Search on 11 Oct 2026, at 10:24 in “New AI enzymes, 700+ math breakthroughs, AI for DNA mutations, room temp semiconductors: AI NEWS”.
Sources: the vendor's own pages (linked above) and creator videos at the linked timestamps. EU status is information, not legal advice; see how we check.
BOTANIC-1 is a genetic language model (GLM), described as a plant genomic world model, built by the Paris-based AI biology lab Living Models. It is pre-trained across 320 plant species and is meant to capture evolutionary constraints in plant genomes. Google DeepMind features it on its Gemma "Gemmaverse" pages as an example of Gemma 4 being used in a domain-specific pipeline.
In the featured pipeline, Gemma 4 E4B acts as an agentic orchestrator. It translates natural-language questions into structured queries against BOTANIC-1's inference endpoints, and it also writes bioinformatics pipelines and runs tool calls. BOTANIC-1 scores candidate mutations. In a melon test, the CmEIN3 gene (flower sex) was narrowed from 47,492 genome-wide variants to 3,061 regional candidates. A creator summary says the model ranked the correct mutation first among about 2,500 candidates 90% of the time. The source page compares this against a classical-tools setup (bcftools, Ensembl VEP). That setup in its best runs left two identically scored coding mutations.
Living Models runs Gemma 4 E4B locally via Ollama on a single NVIDIA L4 GPU, so proprietary genomes stay on the user's own infrastructure. The provided material does not describe public weights, pricing or a public API for BOTANIC-1. It appears to be a research and partner system rather than a general release.
- Genomic language model pre-trained on 320 plant species
- Ranks candidate mutations by evolutionary constraint
- Paired with Gemma 4 E4B as agentic orchestrator via inference endpoints
- Demonstrated on melon CmEIN3 flower-sex trait with INRAE collaborator
- Orchestrator runs locally on a single NVIDIA L4 GPU via Ollama
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