What is Ollama?
Ollama is listed under Local LLM Runners, in the AI Models & Local Execution category on Flocci AI Tools. The default way to run LLMs locally. It is free, with no paid plan attached, and it lives at ollama.com.
What Ollama does
- The default way to run LLMs locally
- One command to run Llama, Qwen, DeepSeek…
- OpenAI-compatible local API
- Free and open-source
Ollama — straight answers
Is Ollama free?
Ollama is listed as fully free — there is no paid tier attached to it in the catalog. That makes it one of the 115 entries on Flocci AI Tools with no upgrade path built in.
What can Ollama do?
Ollama does 4 things the catalog singles out: The default way to run llms locally; one command to run llama, qwen, deepseek…; openai-compatible local api; free and open-source.
What is the best free alternative to Ollama?
AnythingLLM is the closest free alternative: it sits in the same Local LLM Runners sub-category and is free. GPT4All, Jan and KoboldCpp also start free. The full list is on the alternatives page.
See the full list →Ollama alternatives
Compare all alternatives →LM Studio
Local LLM Runners
- Polished desktop GUI for local models
- Discover, download and chat with GGUF models
- Local server with OpenAI-compatible API
- Free for personal use
Jan
Local LLM Runners
- Open-source, offline ChatGPT alternative
- No-config, privacy-first GUI
- Runs fully on your device
- Free forever
GPT4All
Local LLM Runners
- Private local chat with your documents
- Runs on modest laptops
- LocalDocs RAG built in
- Free and open-source
Open WebUI
Local LLM Runners
- Self-hosted ChatGPT-style interface
- Works with Ollama and OpenAI-compatible APIs
- RAG, tools and multi-user
- Free and open-source
AnythingLLM
Local LLM Runners
- All-in-one local RAG and agents app
- Chat with your docs privately
- Works with local or cloud models
- Free and open-source
llama.cpp
Local LLM Runners
- Pure C/C++ inference engine with minimal dependencies, runs on CPU-only hardware
- Powers the GGUF format used by Ollama, LM Studio and most local runners under the hood
- Broad quantization support (2-bit to 8-bit) for running large models on consumer hardware