RAG vs Fine-Tuning Infographic Brief
Purpose
Visual side-by-side comparison helping businesses decide between RAG and fine-tuning for their AI project.
Brand Specs
- Primary colour: #000066 (navy)
- Accent colour: #9333ea (purple)
- Display font: Instrument Serif (headings)
- Body font: Plus Jakarta Sans (data, labels)
- Background: White (#FFFFFF) with subtle navy gradient at top
- Card style: Rounded corners (16px), light navy border
Visual Layout
Header (top 15%)
- Title: “RAG vs Fine-Tuning”
- Subtitle: “Which approach does your business need?”
- SIAGB logo top-right
Main Comparison Grid (60%)
Two columns (RAG left in navy, Fine-Tuning right in purple) with rows:
| Dimension | RAG | Fine-Tuning |
|---|---|---|
| Best for | Accessing current, specific information | Changing model behaviour and style |
| Setup cost | $5,000 - $30,000 | $10,000 - $100,000+ |
| Setup time | 2 - 6 weeks | 4 - 12 weeks |
| Data freshness | Always current (real-time retrieval) | Frozen at training time |
| Hallucination risk | Lower (grounded in source docs); reduces hallucinations by 40-70% | Moderate (no source verification); can increase hallucination with poor data |
| Ongoing cost | $200 - $2,000/month (infrastructure) | Low (inference only) until retrained |
| Transparency | High (can cite sources) | Low (baked into weights) |
| Data needed | Your existing documents and databases | Curated training examples (hundreds to thousands) |
| Update frequency | Instant (update docs, answers change) | Requires retraining |
| Technical complexity | Moderate | High |
Year One Total Cost Comparison (callout boxes)
- RAG Year One: $12,000 - $75,000 (Initial build $8K-$25K + Vector DB $50-$500/mo + Compute $100-$1,500/mo + Maintenance $500-$2,000/mo)
- Fine-Tuning Year One: $15,000 - $130,000 (Data prep $5K-$20K + Training $500-$50K + Hosting $200-$5,000/mo + Retraining $2K-$20K/yr)
- Combined Year One: $25,000 - $180,000
ROI Timeline (callout bar)
- RAG: Measurable ROI within 4 - 8 weeks of deployment
- Fine-Tuning: ROI in 2 - 4 months
- Combined: 3 - 6 months to fully mature, highest long-term returns
Decision Box (15%)
Choose RAG if…
- Your information changes frequently (product catalogues, pricing, policies)
- You need source citations for compliance (healthcare, legal, finance)
- Accuracy matters more than style
- You want to get started quickly (weeks, not months)
Choose Fine-Tuning if…
- You need a specific brand voice, tone, or terminology
- You’re doing a specialised task repeatedly (classification, extraction, code generation)
- Latency is critical (RAG adds 200-500ms retrieval step)
- Your training data is stable (medical terminology, legal frameworks)
Choose Both if…
- You need behaviour/style changes AND current information access
- You’re building enterprise-grade AI (fine-tune for reasoning, RAG for live data)
CTA Bar (10%)
- Navy (#000066) background, white text
- “Need help deciding? Talk to our AI team”
- URL: siagb.com.au/contact/