# Ollama vs RSS Filter Ollama records 9,421,973 monthly visits with +4.3% month-over-month growth and Free, Freemium, Paid pricing. RSS Filter records 0 monthly visits with 0% growth and Free pricing. | Metric | [Ollama](https://openaitools.app/tool/ollama) | [RSS Filter](https://openaitools.app/tool/rss-filter) | | :--- | :--- | :--- | | Website URL | https://ollama.com | https://rssfilter.sgn.space | | Categories | Large Language Models (LLMs), AI Developer Tools, Open Source AI Models | Large Language Models (LLMs), AI Productivity Tools, AI Assistant | | Pricing Model | Free, Freemium, Paid | Free | | Monthly Visits | 9,421,973 | 0 | | MoM Growth Rate | +4.3% | 0% | | Primary Market | China | Global | | Direct Visits | 4,020,134 | 0 | | Review Score | 4.8 | 4.5 | | Saved Count | 0 | 0 | | Supported Platforms | app, open-source, website | Website | ## Ollama Ollama has become the default way many developers get started with open models. A single install gives you a local server and a command line that pulls model weights, manages versions, and exposes a simple HTTP API on your machine. Because everything runs locally, prompts and responses never leave your computer, which makes it a natural fit for privacy-sensitive prototyping, offline work, and experiments that should not be metered per token. The project has expanded well beyond a local runtime. Ollama now also serves open models in the cloud, so you can reach larger or more capable checkpoints without owning a high-end GPU. The company reports over nine million monthly installs, more than a billion model downloads, and hundreds of trillions of tokens served, which reflects how widely the tool is embedded in AI developer workflows. Pricing stays approachable: running models on your own hardware is free and unlimited, while cloud usage is metered per token, with subscription plans for individuals, power users, and teams. Model weights are supplied by the upstream publishers, and Ollama states that prompt and response data are never logged or used for training. **Pricing & Plans:** 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. - **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. - **Privacy by default:** Local inference keeps prompts and outputs on your own device, with no logging or training on your data. **Strengths:** 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 **Limitations:** Local performance depends heavily on your GPU and RAM; Cloud usage is billed per token and large models add up quickly; Advanced serving features are less extensive than dedicated inference servers [Profile (Markdown)](https://openaitools.app/tool/ollama.md) ## RSS Filter RSS Filter targets a familiar problem: the feeds pile up faster than anyone can read. Rather than another reader, it is a filtering layer that sits between your feeds and your client. The idea is simple - instead of seeing every item, you see a curated subset that matches what you have already shown interest in. The recommendation engine is built on LLM embeddings and machine learning. As you read articles, the system tracks them and learns which topics matter to you, then ranks and filters new items by semantic similarity. Because it works by replacing the original feed URLs, you do not need to switch readers or change your existing habits; you simply point your client at the filtered sources. Getting started takes an OPML upload. Export your subscriptions from whatever reader you use, drop the file onto the site, and it returns a set of filtered feed URLs. The project is open source - the code lives on GitHub under m0wer/rssfilter - and it is free to use, with a public email contact for feedback. It is the kind of lightweight utility that is best judged by whether it quietly makes your feed manageable again. **Pricing & Plans:** Free to use. RSS Filter is a free tool and open-source project; there are no paid tiers advertised on the site. - **One-Click OPML Conversion:** Upload an OPML export from your RSS client and get all your existing feeds converted into filtered versions automatically. - **Learning From Your Reads:** Every read article feeds a machine-learning model, so recommendations adapt to your real interests over time. - **LLM Embedding Recommendations:** LLM embeddings compare semantic similarity between articles rather than relying only on keywords or categories. - **Works With Any RSS Client:** It works by swapping your original feed URLs, so you keep using your preferred RSS reader with no new app to learn. - **Open Source and Free:** The project is open source on GitHub and can be reported or contacted through a public email address. **Strengths:** Completely free and open source; Works by swapping feed URLs, so no new reader is needed; Learns from your actual reading behaviour rather than static rules; OPML upload makes converting an existing feed list quick [Profile (Markdown)](https://openaitools.app/tool/rss-filter.md) ## Frequently Asked Questions ### How do Ollama and RSS Filter compare in monthly traffic? Ollama has 9,421,973 monthly visits, while RSS Filter has 0. Traffic estimates describe audience size, not product quality. ### How do their growth rates compare? Ollama has a month-over-month growth rate of +4.3%; RSS Filter has 0%. ### 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. RSS Filter: Free. Free to use. RSS Filter is a free tool and open-source project; there are no paid tiers advertised on the site. ## Alternatives | # | Tool Name | Monthly Visits | MoM Growth Rate | Pricing Model | Summary | Profile (Markdown) | | :--- | :--- | :--- | :--- | :--- | :--- | :--- | | 1 | [DeepSeek](https://openaitools.app/tool/deepseek) | 372,761,591 | +4.3% | Freemium | High-efficiency open-weight and hosted reasoning AI powered by DeepSeek-V4 and R1 at ultra-low token costs. | [.md](https://openaitools.app/tool/deepseek.md) | | 2 | [OpenRouter](https://openaitools.app/tool/openrouter-ai) | 19,941,437 | -6.2% | Paid | Cloud API gateway providing instant access to thousands of models, trading local hardware privacy for cloud compute. | [.md](https://openaitools.app/tool/openrouter-ai.md) | | 3 | [The StoryGraph](https://openaitools.app/tool/thestorygraph-com) | 5,691,605 | +4.5% | Freemium | Mood-based book recommendations and reading tracking | [.md](https://openaitools.app/tool/thestorygraph-com.md) | | 4 | [Kagi Search](https://openaitools.app/tool/kagi-search) | 4,647,605 | +3.2% | Free Trial, Paid | A paid, ad-free search engine that answers to its users | [.md](https://openaitools.app/tool/kagi-search.md) | | 5 | [Clawdbot (OpenClaw)](https://openaitools.app/tool/clawdbot) | 1,903,068 | -25.4% | Paid, Free | Open-source personal AI assistant that runs on your own machine and works from chat apps | [.md](https://openaitools.app/tool/clawdbot.md) | | 6 | [Dify](https://openaitools.app/tool/dify-ai) | 819,691 | -15% | Freemium | Open-source platform for building visual agentic workflows and RAG pipelines using local or cloud models. | [.md](https://openaitools.app/tool/dify-ai.md) | | 7 | [Open WebUI](https://openaitools.app/tool/open-webui) | 804,534 | -2.8% | Freemium | Self-hosted AI workspace for local and cloud models | [.md](https://openaitools.app/tool/open-webui.md) | | 8 | [AnythingLLM](https://openaitools.app/tool/anythingllm) | 512,269 | +12.9% | Freemium | Own your intelligence: a private AI assistant that runs entirely on your machine | [.md](https://openaitools.app/tool/anythingllm.md) | | 9 | [LlamaIndex](https://openaitools.app/tool/llamaindex) | 387,910 | +19.9% | Freemium, Contact for Pricing | Development framework for connecting local models to external document stores and structured data sources. | [.md](https://openaitools.app/tool/llamaindex.md) | | 10 | [Jan](https://openaitools.app/tool/jan) | 291,894 | -9.6% | Free | Open-source desktop app for running models locally with a graphical interface, but heavier than Ollama's lightweight CLI. | [.md](https://openaitools.app/tool/jan.md) | --- Source: https://openaitools.app/compare/ollama-vs-rss-filter More Markdown: [Categories](https://openaitools.app/categories.md) · [Traffic rankings](https://openaitools.app/rankings.md) · [llms.txt](https://openaitools.app/llms.txt)