LlamaIndex

• CPU-only box: 8 cores, 15 GB RAM, no GPU.
• Toy corpus

LlamaIndex's local RAG quickstart worked at $0 with no keys. It indexed in about a second, answered all three factual questions from the right document, and said it didn't know the CEO's favorite color instead of making something up. The corpus was tiny, so this shows it works, not how well it retrieves at scale.

4/4 on a local, offline RAG check. Toy corpus.

Coverage

Local RAG quickstart: 4 docs, 3 factual questions, 1 unanswerable

What we tested

Fully local RAG quickstart: 4 small docs, 3 factual questions and 1 unanswerable question.

Method

llama-index-core with Ollama LLM qwen2.5-coder-3b and nomic-embed-text v1.5 embeddings, VectorStoreIndex, top_k=2, all on CPU.

Prompts

1. What is the office cat's name?
2. On which day are new tool tests published?
3. How much RAM does the test box have?
4. What is the CEO's favorite color?

Measured

• index_build_s1.1
• catThe office cat's name is Pixel. 7.2 s, passed
• publish dayNew tool tests are published every Tuesday at 9 AM Central. 2.4 s, passed
• ramThe test box has 15 GB of RAM. 1.7 s, passed
• ceo colorBased on the provided context information, there is no mention of a CEO or their favorite color. The information given i. 3.6 s, passed
• pass4/4 (the refusal was graded by hand; the auto keyword check missed 'no mention')

Raw test log