Terraform vs Modal
Side-by-side comparison of AI visibility scores, market position, and capabilities
Acquired by IBM $6.4B Feb 2025 (HashiCorp); $646M revenue expected FY25; 500M+ downloads; 85% Fortune 500; integrated with Red Hat Ansible; IaC leader
About
Terraform is an open-source infrastructure-as-code tool originally created by HashiCorp, founded in 2012 in San Francisco by Mitchell Hashimoto and Armon Dadgar. Terraform introduced a declarative configuration language (HCL) that allowed engineers to define, provision, and manage cloud infrastructure across any provider — AWS, Azure, Google Cloud, and hundreds of others — through version-controlled configuration files. It became the de facto standard for cloud infrastructure automation and gave rise to the IaC category as it is known today.\n\nTerraform's core capability is its provider ecosystem, with 3,000+ providers enabling teams to manage infrastructure, SaaS services, and on-premises systems from a single workflow. HashiCorp built Terraform Cloud and Terraform Enterprise on top of the open-source tool, adding team collaboration, remote state management, policy enforcement, and audit features for enterprise deployments. With 500M+ downloads and adoption by 85% of Fortune 500 companies, Terraform became one of the most widely used developer tools in cloud infrastructure.\n\nIn February 2025, IBM completed its $6.4B acquisition of HashiCorp, bringing Terraform under IBM's portfolio alongside Red Hat and other enterprise infrastructure products. FY2025 revenue for HashiCorp was projected at approximately $646M. The acquisition reflects Terraform's strategic importance in the hybrid cloud era and IBM's intent to integrate IaC capabilities into its broader cloud and automation platform. Despite a 2023 license change from MPL to BSL that sparked the OpenTofu fork, Terraform's commercial ecosystem and enterprise installed base remain dominant.
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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