AbCellera vs Modal
Side-by-side comparison of AI visibility scores, market position, and capabilities
Vancouver-based antibody discovery platform with 104+ partner programs; $75M FY2025 revenue. Expanding into wholly owned assets with ABCL635 in Phase 1 for vasomotor symptoms.
About
AbCellera Biologics was founded in 2012 in Vancouver, Canada by Carl Hansen, growing out of research at the University of British Columbia. The company built a high-throughput antibody discovery platform integrating microfluidics, genomics, single-cell sequencing, and AI/ML to rapidly identify therapeutic antibody candidates from natural immune responses. AbCellera played a prominent role in the COVID-19 pandemic by discovering bamlanivimab for Eli Lilly in under 90 days.\n\nAbCellera's partnership model operates on a discovery fee plus downstream milestone and royalty structure, having started over 104 partner-initiated programs with downstream participation as of December 2025. Partners include major pharmaceutical companies and biotechs; the company expanded its collaboration with AbbVie in 2025 to develop T-cell engagers for oncology. Total FY2025 revenue was $75 million ($47M from royalties/licensing, $27M from partnered program work), compared to $29 million in 2024—a dramatic increase driven by royalty flows from approved medicines.\n\nIn 2025 AbCellera began transitioning from pure partnership model toward wholly owned therapeutic assets, with ABCL635 (a GnRH receptor antibody for vasomotor symptoms) entering Phase 1. The company maintains approximately $700 million in liquidity, providing a long runway. AbCellera is considered a foundational infrastructure provider for the antibody-based drug discovery ecosystem.
Serverless GPU cloud platform for AI/ML with Python-native deployment and per-second billing; developer-favorite scaling from zero competing with Replicate and Beam for AI compute.
About
Modal is a serverless cloud computing platform purpose-built for AI and machine learning workloads — providing on-demand GPU compute that scales instantly from zero with per-second billing, container management, distributed training support, and a Python-native developer experience that makes running ML workloads in the cloud feel as simple as running code locally. Founded in 2021 in New York City and backed by Redpoint Ventures and other investors, Modal has grown rapidly as AI development has accelerated demand for flexible, developer-friendly GPU infrastructure.\n\nModal's developer experience is its primary differentiator — engineers write Python functions decorated with @modal.function() and deploy them to the cloud with a single command, with Modal handling container building, GPU provisioning, auto-scaling, and execution. The platform supports training jobs that need distributed compute across multiple GPUs, model serving endpoints that scale to zero when unused (eliminating idle GPU costs), and batch inference jobs that process large datasets. The per-second billing model means developers pay only for actual compute time, not provisioned instances.\n\nIn 2025, Modal competes in the AI infrastructure market with Replicate, Beam, Banana, and major cloud providers' managed ML services (AWS SageMaker, Google Vertex AI, Azure ML) for serverless GPU compute. The market for AI-specific cloud infrastructure has grown dramatically as the number of ML engineers deploying models to production has expanded — traditional cloud providers require significant DevOps expertise to use GPU instances effectively, while Modal's Python-native approach reduces the barrier to entry. Modal has attracted a strong developer following among AI researchers and ML engineers building production AI applications. The 2025 strategy focuses on growing the developer community, adding enterprise features (dedicated GPU capacity, private networking, compliance), and expanding the hardware options available (H100 GPUs, custom accelerators).
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