Ollama vs Replicate
Both are ai tools. Here is what separates them.
What Ollama is
Ollama runs open weight language models on your own machine, and optionally on Ollama's hosted cloud. Models are pulled down and driven from a command line interface, and the same models can be called over an HTTP API, so one installation serves both a terminal chat and an application. Installers are published for macOS, Windows and Linux, with the macOS build requiring macOS 14 Sonoma or later, and the whole thing can be installed with a single shell command that pipes the vendor's install script into sh. A model is started with ollama run, and a chat session ends by typing the bye command. The rest of the CLI covers pull, rm, ls, ps, stop, serve, signin, signout and launch. The launch command wires Ollama models into external tools including VS Code and several coding agents. Custom models are defined in a Modelfile and built with ollama create. The local API listens on port 11434 at localhost. There is also an OpenAI compatible layer that accepts the literal string ollama as the API key and covers chat completions, completions, models, embeddings and responses endpoints. That layer has gaps worth knowing about before you point an existing client at it: it does not support logprobs, logit bias or tool choice, and images must be base64 encoded rather than passed as URLs. Appending a cloud suffix to a model name runs that model on Ollama's cloud instead of locally, which requires signing in with the ollama signin command or setting an API key in the OLLAMA_API_KEY environment variable. The hosted API is reachable at ollama.com/api, and cloud models are served from the United States, Europe and Singapore. Cloud features can be turned off entirely so that an installation runs only against local models, which then work with no network connection at all. Cloud use is what the paid plans meter. The Free plan costs nothing, allows one cloud model to run at a time and permits an unlimited number of public models. Pro costs 20 USD per month or 200 USD per year, raises the limit to three cloud models at a time and permits uploading and sharing private models. Max costs 100 USD per month and allows ten cloud models at a time. Team costs 25 USD per seat per month with a five seat minimum and includes zero data retention. Enterprise pricing is quoted rather than listed. Ollama states that user data is not used to train models.
What Replicate is
Replicate runs machine learning models behind a cloud API, so the user never provisions or manages a GPU. Models are packaged with Cog, an open source tool that wraps a model in a container with a generated API server. A deployment scales with demand and scales down to zero when it is idle. The HTTP API sits at https://api.replicate.com/v1 and authenticates with an API token sent in the Authorization header using the Bearer scheme. Endpoints cover predictions, models, model versions, deployments, trainings, hardware and account, and a running prediction or training can be stopped through a dedicated cancel endpoint. Webhooks give asynchronous completion notifications and streaming output is supported. Client libraries are published for Python and Node.js alongside the plain HTTP API. Creating a prediction is rate limited to 600 requests per minute and every other endpoint to 3,000, with an HTTP 429 returned past either limit. Fine tuning is done by calling the trainings API with a base model and a training dataset, which produces a new deployable model version. Model output files are served from the replicate.delivery domain and its subdomains, and prediction inputs, outputs and logs created through the API are deleted after one hour by default. Billing is per second of compute at a rate set by the hardware chosen. Standard CPU compute is $0.0001 per second, or $0.36 an hour, an Nvidia T4 is $0.000225 or $0.81 an hour, an Nvidia L40S is $0.000975 or $3.51 an hour, and a single Nvidia H100 is $0.001525 or $5.49 an hour. An Nvidia A100 with 80GB of memory costs $5.04 an hour, and an eight way H100 configuration costs $0.0122 per second, which works out at $43.92 an hour. Some models are priced per unit of output instead: Flux 1.1 Pro at $0.04 per generated image, Flux Schnell at $3.00 per thousand images, and Wan 2.1 image to video at 720p at $0.25 per second of output. Private models are billed for their entire running time, including boot and idle, while fast booting fine tunes are billed only for active processing.
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