Running local LLMs for code generation and AI assistants, Experimenting with many open models locally without API keys, Providing infrastructure for companies to run their own models to avoid API costs
It's the easiest way to run open-source AI models locally, but performance depends heavily on your hardware.
Batch processing or high-performance inference where KV cache is needed, Getting accurate, detailed information about model specifications
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I'm happy I invested in setting up Codex CLI and getting it to work with ollama.
Hacker News • HackerNews • Use case: working with Codex CLI to run local models
It's also possible to make an MLX version of it, which runs a little faster on Macs, but won't work through Ollama unfortunately.
Hacker News • HackerNews • Use case: Running an MLX version of a dealigned Gemma model
with ollama and vllm you can just build your own agentic environment IDE, give it the tools you like, and make the workflow however you like.
Hacker News • HackerNews • Use case: building a self-hosted agentic environment IDE for coding
the LLM searches for the right endpoint by keyword (or optional semantic search via Ollama), gets back the method path params, then calls it through a generic proxy.
Hacker News • HackerNews • Use case: Optional semantic search backend for the MCP server to help the LLM find the correct API endpoint.
I have Ollama installed on my Linux desktop with Alpaca as the frontend, but honestly I haven t done much with it beyond poking around.
Hacker News • HackerNews • Use case: Running local AI models on a Linux desktop
Ollama is a full 25% faster. I averaged 24.4 t/s on Ollama and 19.45 t/s on LM Studio for the same ~10 GB model.
Hacker News • HackerNews • Use case: Benchmarking inference speed for a local Gemma 4 model
I'm using it as the backend for playing with other frontend stuff and it seems to work just fine. The issue is that they try to abstract away a bit too much, especially when LLM model quality is highly affected by a bunch of parameters.
Hacker News • HackerNews • Use case: Backend for playing with other frontend stuff
Can I use your tool with local models like gemma 4 and ollama llama.cpp: I have 3 24gb Nvidia cards and would like to try a three agent approach.
Hacker News • HackerNews • Use case: Running local models, specifically mentioned as an alternative to cloud-based CLI tools.
Ollama felt like more of a bottleneck than the model itself.
Hacker News • HackerNews • Use case: Running Gemma model locally on Apple Silicon
You can run the quantized model on ollama... and you're good to go.
Hacker News • HackerNews • Use case: Running the quantized Gemma 4 26B model for inference
tricked people. Only way to win is to uninstall it.
Hacker News • HackerNews • Use case: as an easy frontend for llama.cpp
It mangles GGUF files so other apps can't use them, and you can't access them either without a bunch of work on your end. This is what pushed me away from Ollama.
Hacker News • HackerNews • Use case: Running and managing local LLM models (GGUF files)
Local models (like Llama 3 or Mistral via Ollama) – handy if you’re into running things offline.
Hacker News • HackerNews • Use case: running local models (like Llama 3 or Mistral) offline
OpenAI and i think nowaday ollama compatible endpoints allow me to use it in VSCode Copilot as well as i.e. Open Web UI.
Hacker News • HackerNews • Use case: compatible endpoint standard for connecting tools like lemonade
Works with Ollama too for fully local.
Hacker News • HackerNews • Use case: Running models fully locally, integrated with the described workflow
I have my best results with Ollama using deepseek-r1. That way I have my ai no matter the internet connection or big tech s decisions.
Hacker News • HackerNews • Use case: Running local AI models (deepseek-r1) for offline, independent AI capabilities
Also wrote an OpenAI Ollama Claude proxy that allows using on-prem models running on another server through Ollama llama.cpp and also using AWS Bedrock models when permissions are configured.
Hacker News • HackerNews • Use case: Used to run on-prem models on another server via a custom proxy.
Put together a guide to use LLMStack with Ollama last week for using local models.
Hacker News • HackerNews • Use case: Running local models (like Llama 3) as part of the RAG application stack
AI agents (running local LLMs like Ollama) are moving from generating text to executing physical, financial, and network state changes.
Hacker News • HackerNews • Use case: Running local LLMs as the 'Brain' for AI agents that generate intents/aspirations.
Even experimenting with small local LLMs like Deepseek R1:8B via Ollama. Though that brings the systems to their limits... But still, while doing so, music from YT doodling on... System stays responsive.
Hacker News • HackerNews • Use case: Running local LLMs (Deepseek R1:8B)
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