Earthly vs Modal
Side-by-side comparison of AI visibility scores, market position, and capabilities
Earthly runs build steps in containers via Earthfile syntax, eliminating inconsistencies between local and CI environments for reproducible, parallelizable builds across any stack.
About
Earthly is an open-source build automation framework that runs build steps inside containers, ensuring that builds produce identical results on developer laptops and in CI systems regardless of the underlying environment. Earthly's Earthfile syntax combines familiar concepts from Dockerfile and Makefile, making it approachable to teams already using containers without requiring deep build system expertise. The containerized execution model eliminates the classic "works on my machine" problem by ensuring every dependency is pinned and every environment is identical. Earthly supports parallel execution of independent build targets and efficient layer caching to minimize build time. The company offers Earthly Satellites, a managed remote build service, for teams that need consistent build performance in CI. Founded in 2020 with backing from Uncork Capital and 468 Capital, Earthly has gained adoption among developer teams frustrated with the complexity of existing CI systems and the inconsistency of language-specific build tools. It competes with Bazel, Make, and language-specific build systems in the reproducible build market.
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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