What it is
Ollama makes running an open model on your own computer a one-line job: `ollama run` plus a model name downloads the weights and starts a chat. It runs on macOS, Windows and Linux, and as an official Docker image.
It exposes a local REST API on port 11434, including an OpenAI-compatible endpoint, and `ollama launch` wires local or cloud models into coding agents such as Claude Code, Codex, Copilot CLI and OpenCode. A curated library lists models such as Gemma 4, gpt-oss, Qwen and DeepSeek.
The company also sells Ollama Cloud for larger models it hosts, mainly in the United States. Its pricing page says running models on your own hardware stays unlimited and that cloud prompts and responses are never logged or used for training.
Our review
Ollama is the shortest route from nothing to a working local model, and its defaults are tuned for one person on one machine. It has about 184,400 GitHub stars and ships almost daily: v0.40.9 on 22 October 2026 was its fifth release in nine days.
Its appeal is that it removes setup. Model downloads, GPU detection and a background server are handled for you, and so many editors, chat apps and agent tools list Ollama as a backend that it has become the default local API. The defaults deserve a second look, though. Per the FAQ, the context window is 4,096 tokens unless you raise it, which is too small for a coding agent reading several files, each model handles one request at a time, and memory use grows with parallel requests multiplied by context length.
The security story is about configuration, not code quality. Ollama binds to 127.0.0.1 with no authentication; setting OLLAMA_HOST to 0.0.0.0 exposes the whole API, and in January 2026 SentinelOne and Censys counted 175,000 publicly reachable servers. In May 2026 CVE-2026-7482, a heap out-of-bounds read rated 9.1 that leaks process memory in three unauthenticated calls, was disclosed and fixed in v0.17.1. Any instance that was reachable from the internet before patching should have its secrets rotated.
The company now sells a cloud: Pro is $20 a month with $60 of credits and three concurrent requests, Max $100 with $300 and ten, and Team $500 with $1,000 of shared credits and unlimited users. Setting OLLAMA_NO_CLOUD=1 switches the cloud off entirely. Against llama.cpp, Ollama gives up tuning knobs for convenience; against vLLM it gives up multi-user throughput for a one-line install, and for a single developer both trades are sensible.
Where it earns its place
A developer on an Apple Silicon laptop who wants a private coding assistant
Run a coding agent against a local model so code never leaves the machine
ollama launch claude or ollama launch codex points the agent at a local model. Raise OLLAMA_CONTEXT_LENGTH well above the 4,096-token default or the agent loses track of files; there is no cost beyond the hardware you own.
The IT lead at a law firm handling confidential documents
Let staff summarise documents without sending them to a cloud API
Run Ollama on a GPU workstation with a chat front end such as Open WebUI. Keep it bound to localhost or behind an authenticating reverse proxy, because the API has no login, and set OLLAMA_NO_CLOUD=1 so nobody routes a document to hosted models by accident.
A ten-developer team whose laptops cannot hold the largest open models
Use bigger hosted open models through the same Ollama API
The Team plan at $500 a month includes $1,000 of shared credits, unlimited users and ten concurrent requests; usage beyond that draws from a shared pay-as-you-go balance. Cloud models run mainly in the US and may route to Europe.
Before you commit
- Setup
- One install script (curl on macOS and Linux, PowerShell on Windows) or the ollama/ollama Docker image, then ollama run gemma4. The API listens on localhost:11434 immediately.
- Integrations
- REST API with an OpenAI-compatible endpoint, official Python and JavaScript libraries, and ollama launch for Claude Code, Codex, Copilot CLI, Droid and OpenCode; most local chat apps support it.
- Data and privacy
- Local prompts never leave the machine; models are stored under ~/.ollama/models. Ollama Cloud says it neither logs nor trains on prompts and requires zero-retention hosting partners. GitHub lists no advisories, but CVE-2026-7482 (CVSS 9.1) affected versions before 0.17.1.
- Cost at scale
- Local use costs only hardware. Cloud: Pro $20 a month ($60 credits, 3 concurrent), Max $100 ($300, 10 concurrent), Team $500 ($1,000 shared, unlimited users); unused credits do not roll over, and off-peak pricing applies outside 12:00 to 18:00 UTC on weekdays.
- Limits
- 4,399 open issues and pull requests. Defaults of one parallel request per model and a five-minute keep-alive suit single users; heavy concurrent traffic belongs on vLLM or SGLang.
What's good
- One-line install and model management on macOS, Windows and Linux
- Local API supported by most editors and agent tools
- ollama launch connects Claude Code, Codex and OpenCode to local models
- Local use is free and unlimited; cloud can be disabled
What's not
- No authentication; exposing port 11434 is a common, costly mistake
- 4,096-token default context is too small for agent work
- One request per model by default; not built for multi-user serving
Best for
Developers and individuals who want open models running locally with minimal setup.
Alternatives
Ollama: common questions
- Is Ollama worth it?
- Local models in one command, with defaults (a 4,096-token context, one request at a time, no login) that suit a laptop and nothing bigger. We rate it 4.6 out of 5.
- How much does Ollama cost?
- Open source (MIT) and free to run locally. Optional Ollama Cloud: Free with starter credits; Pro $20/month ($60 credits); Max $100/month ($300 credits); Team $500/month ($1,000 shared credits, unlimited users); Enterprise custom.
- What are the downsides of Ollama?
- No authentication; exposing port 11434 is a common, costly mistake; 4,096-token default context is too small for agent work; one request per model by default; not built for multi-user serving.
- Who is Ollama best for?
- Developers and individuals who want open models running locally with minimal setup.
- How much does Ollama cost for a team or in production?
- Local use costs only hardware. Cloud: Pro $20 a month ($60 credits, 3 concurrent), Max $100 ($300, 10 concurrent), Team $500 ($1,000 shared, unlimited users); unused credits do not roll over, and off-peak pricing applies outside 12:00 to 18:00 UTC on weekdays.
- Is Ollama safe for company data?
- Local prompts never leave the machine; models are stored under ~/.ollama/models. Ollama Cloud says it neither logs nor trains on prompts and requires zero-retention hosting partners. GitHub lists no advisories, but CVE-2026-7482 (CVSS 9.1) affected versions before 0.17.1.
- What are the best Ollama alternatives?
- The closest alternatives we have reviewed are llama.cpp, llamafile, MLX and vLLM.
Answers checked Oct 23, 2026.
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