AI Tool Guides
Best for
Running a frontier AI model locally for free
Works on
Local (via Ollama), Linux, macOS
Alternatives
Mistral, Qwen
Watch out
10M context window but needs 32GB+ RAM for larger variants
What It Does
Meta's LLaMA (Large Language Model Meta AI) is the most widely adopted open-weight language model family. LLaMA 4 Scout (17B active parameters, 16 experts) and Maverick (17B active, 128 experts) offer performance competitive with GPT-4o and Claude Sonnet on many benchmarks—but you can download the weights, run the model on your own hardware, fine-tune it on your data, and inspect its behaviour. No API key, no usage fees, no data sent to a third party.
Setup in 5 Minutes
).
- Install Ollama, then run ollama run llama4 in your
terminal.
- The model downloads once and runs locally.
- For fine-tuning or research, download weights from
llama.meta.com (requires acceptance of Meta's licence) or
from Hugging Face.
- Cloud providers (AWS, Azure, Google Cloud) also host LLaMA models
with pay-per-token pricing.
Try This
Install Ollama and run LLaMA 4 Scout locally. Ask it the same question you
would ask ChatGPT and compare the quality. Then try a privacy-sensitive
task—summarising a confidential document, analysing personal financial
data, or drafting a sensitive email. Notice the difference: the data never
leaves your machine. Check the model's speed on your hardware and compare
it with the API response time.
Follow Along
Follow Along — Privacy-First Document Analysis:
.
- Ask follow-up questions: "What are the termination clauses?" and "Are there any unusual or potentially unfair terms?"
- Verify that no network requests were made during the session (disconnect Wi-Fi if you want absolute certainty).
- Compare the summary quality with what you would get from ChatGPT—but note that with LLaMA, zero data left your machine.
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Open sourceAI Analysis
Frameworks from the aiborg Handbook — powered by Claude