tristanfaure.com /projects / recipe-llm-benchmark
Recipe LLM Benchmark
Qwen3-0.6B: Few-Shot vs RAG vs LoRA fine-tune vs RAG+FT, measured
2026 · ACADEMIC
Stack
Python · Qwen3 · LoRA (PEFT) · RAG · Hugging Face · Embeddings
Key figures
- Strategies
- 4 compared
- Corpus
- 30K recipes
- Metrics
- ROUGE · cosine · latency
- Model
- Qwen3-0.6B
A controlled benchmark of the four ways to specialize a small LLM: few-shot prompting, RAG over 30K recipes (embedding retrieval), LoRA fine-tuning, and RAG combined with fine-tuning.
Every strategy is scored on the same axes — ROUGE-1, semantic cosine similarity, and latency — so the trade-offs are numbers, not opinions.
The trained LoRA adapter ships with the repo; the same model family and adaptation stack later powered the AutoPilot AI chatbot on this site.
Links
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