How do their growth rates compare?

Ollama has a month-over-month growth rate of +4.3%; SmartSuite has +2%.

How does pricing compare?

Ollama: Free, Freemium, Paid. Running models on your own hardware is free. Cloud use is pay-as-you-go per million tokens, with Pro around $20/month, Max around $100/month, Team around $500/month including shared usage credits, and custom Enterprise pricing. Yearly billing discounts are offered. SmartSuite: Freemium. SmartSuite is freemium: a free trial plus a free entry tier are available, with paid plans that scale by users, features and enterprise needs. Detailed pricing is published on the SmartSuite pricing page and quoted for larger organisations.

What are alternatives to Ollama and SmartSuite?

Other tools in related categories include Notion, OpenRouter, Zapier, n8n, Dooray!.

Ollama vs SmartSuite — Traffic (9.42M vs 259.21K), Pricing & Verdict

Open AI Tools

Ollama vs SmartSuite — Traffic (9.42M vs 259.21K), Pricing & Verdict | Open AI Tools

Side-by-Side Traffic & Specification Matrix

Dimension / Metric	Ollama	SmartSuite
Official Domain	ollama.com	smartsuite.com
Pricing Model	Free, Freemium, Paid	Freemium
Monthly Visits	9.42M (9,421,973)	259.21K (259,211)
MoM Traffic Delta	+389.71K (+4.3%)	+5.07K (+2%)
Primary Market & Share	🇨🇳 China (15.9%)	🇺🇸 United States (66.4%)
Direct Visits / mo	4.02M	187.19K
User Rating	4.8	4.3
Supported Platforms	app, open-source, website	Website

Ollama

Run and build with open AI models locally or in the cloud

One-command local models

Install once and pull open-weight models by name; Ollama handles weights, quantization and versioning for you.

Local HTTP API and CLI

A built-in server exposes a straightforward REST API, so scripts, editors and agents can talk to local models with minimal setup.

Cloud models for bigger jobs

Route requests to hosted open models when your laptop cannot hold the checkpoint you need, with per-token pricing and concurrency tiers.

Broad model catalog

Access families such as Llama, Qwen, DeepSeek, Gemma, Mistral and gpt-oss from a single interface.

Strengths & Pros

+Extremely quick to install and use, with a friendly CLI and API
+Local inference means strong privacy and no per-token cost on your own hardware
+Wide, actively updated catalog of open-weight models
+Cloud option scales to larger models without new hardware