I will set up local llm and private gpt with ollama rag on your machine

Local LLMs run on your hardware so your data never leaves your infrastructure. No API keys, no token costs, no cloud dependencies, no rate limits. Tradeoff: you provide the compute. For sensitive data or high volume use, local is often cheaper and more private than API access.

No. With a fully local setup (Ollama plus an open source LLM), your data, prompts, and responses all stay on your hardware. Offline deployments work too. If you choose hybrid (local LLM with cloud API for some tasks), I mark which parts touch the internet so you have full visibility.

Depends on the model. Small 7B models (Llama 3.1 8B, Mistral 7B) run on a laptop with 16GB RAM and a decent GPU or even CPU only. Larger 70B models need 32GB+ RAM and a serious GPU (RTX 4090, A100). Send me your specs and I will recommend the right model.

General questions and conversation: Llama 3.1, Mistral. Code generation: CodeLlama, DeepSeek Coder. Reasoning tasks: Mixtral, DeepSeek R1. Long context: Llama 3.1 extended. Multilingual: Mistral, Qwen. I will benchmark options on your hardware and recommend the best fit.

Yes. I build RAG systems with vector databases (Chroma, FAISS, Weaviate, Qdrant) so your local LLM can answer questions from your PDFs, CSVs, websites, Notion, MongoDB, or any custom data source. Everything runs on your machine.

Yes. I architect deployments to swap between local LLMs and cloud APIs (OpenAI, Anthropic Claude, Google Gemini) by changing one config value. Lets you start local for privacy or cost, then scale to cloud if you need bigger context or speed.

Yes. Standard and Premium include full source code with commercial use rights.

Depends on hardware. A 7B model on RTX 4090 generates 50 to 100+ tokens per second, often faster than ChatGPT. CPU only setups run 5 to 15 tokens per second, slower but workable for batch tasks. I share realistic benchmarks for your specific hardware.

Yes to all three. Linux servers, Windows or Mac laptops, cloud VPS (AWS, GCP, Hetzner, DigitalOcean), and self hosted on prem hardware. Docker containers make the setup portable across any of them.

Please click "Contact me" before ordering. I review your hardware specs, use case, and data sensitivity in about 10 minutes, then quote a custom package. Avoids surprises on both sides.