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It's a split decision.
Choose Docker for building and running containerized applications, using existing images and CI, or isolating AI agents with microVM sandboxes. Choose Ollama to run and customize open-weight models locally, offline, or through its cloud offering, with a local REST API and Python and JavaScript SDKs. They are not direct substitutes: Docker is a container platform, while Ollama is a model runtime and API. Teams can use both, including Ollama’s official Docker image.
01Side by side
| Docker | Ollama | |
|---|---|---|
| Pricing model | Per-user subscriptions; hardened-image plans per repo | Free local runtime; cloud usage credits and subscriptions |
| Free tier | Personal includes 100 Hub pulls/hour and one private repo | $0 subscription for local models; pay-as-you-go cloud option |
| Open source and licence | Platform licence unstated; DHI Community images use Apache 2.0 | MIT-licensed open-source runtime |
| Self-hosting | Local and cloud sandboxes; self-hosting not stated | Self-host locally, offline, on-prem, or in cloud |
| API and SDKs | MCP governance and sandbox controls; no app API described | REST API on 11434; Python and JavaScript SDKs |
| CLI and docs | Docker Desktop; homepage shows sandbox command | CLI manages models; docs catalog integrations |
| Integrations | Images, registries, CI, Claude, MCP, and OCI | 100+ community integrations, including Open WebUI and Continue |
| Deployment model | Local containers and cloud sandboxes | Local, offline, on-prem, self-hosted cloud, and hosted models |
Docker Choose Docker if
- You need container build, ship, and run workflows.
- You need agent sandbox isolation with network and filesystem controls.
- Your stack already uses OCI images, registries, and CI.
Ollama Choose Ollama if
- You want to run open-weight models on your own hardware.
- You need a local REST API and Python or JavaScript SDK.
- You want to customize models with Modelfiles and LoRA adapters.
02Pricing at real usage
Docker Personal is free and includes one user, one Docker Scout-enabled repo, 100 Docker Hub pulls per hour, and one private repo. Pro costs $11 per user monthly or $9 billed annually; Team is $16 monthly or $15 annually, and Business is $24 either way. These plans add features and Testcontainers Cloud runtime minutes, with extra minutes priced at $3 per 100 or $4 per 100 on demand. Docker Hardened Images Community is free; DHI Select starts at $5,000 per repo.
Ollama’s local pay-as-you-go option has no subscription fee and includes three concurrent requests. Cloud plans start with Pro at $20 monthly or $200 annually, with $60 in usage credits. Max is $100 monthly with $300 in credits; Team is $500 monthly with $1,000 shared credits. Ollama says additional credits are available but does not publish their prices.
03API, SDKs and integration
Docker’s integration story centers on the container stack: its homepage says teams can use existing images, registries, and CI, and describes OCI compliance and platform independence. For agents, Docker offers sandbox controls for network and filesystem access, plus governance for sandbox and MCP policy. The homepage shows a local sandbox command and a path from laptop to Cloud Sandboxes; it does not describe an application API or SDK.
Ollama runs a background service with a local HTTP REST API on port 11434 for completions, chat, and embeddings. It has OpenAI-compatible and Anthropic-compatible endpoints, plus official Python and JavaScript SDKs. Its CLI can pull, run, list, copy, stop, and delete models. Modelfiles configure model weights, prompts, inference settings, templates, and LoRA adapters. The documentation catalogs more than 100 community integrations, including Open WebUI, Continue, LangChain, and LlamaIndex.
04Open source, self-hosting and lock-in
Ollama is open source under the MIT licence and supports self-hosting on local workstations, offline or air-gapped systems, on-premises GPU infrastructure, and cloud environments. Its homepage says prompts and outputs are not stored or used for model training. Docker’s platform licence and self-hosting options are not stated; Docker does list free DHI Community images under Apache 2.0.
For portability, Docker says it is OCI-compliant and works with existing images, registries, and CI. Ollama’s compatible endpoints can reduce application changes when switching between supported APIs, and its official Docker image offers a container deployment option. Neither vendor publishes a dedicated data-export workflow. Check how your chosen deployment stores model files, configurations, logs, and credentials before planning a migration.
Questions people ask
Is Ollama built on Docker?
No. Ollama is an open-source runtime for running and customizing models. It also provides an official Docker image, so you can run Ollama in a Docker container. That packaging option does not make Ollama a component built on Docker.
What is the difference between Docker and a VM?
Docker provides tools for building and running containerized applications. Its agent sandboxes use microVM isolation, with network and filesystem controls. Those sandboxes are a specific Docker offering; the comparison is not a claim that all Docker containers are virtual machines.
Is Docker still relevant in 2026?
Docker fits teams building and running containerized applications with existing images, registries, and CI. Its homepage also describes microVM agent sandboxes and governance. Ollama serves a different role: running and customizing open-weight models, locally or in the cloud.
What are some alternatives to Docker containers?
Ollama is not a general alternative to Docker containers; it is a model runtime. It can run locally or in the cloud, and its official Docker image can run inside a container. The two tools can therefore be used together rather than as replacements.