Model Migration ROI Calculator
Calculate the payback period and 12-month net benefit of migrating from one LLM to another. Factor in engineering hours, quality risk, and exact token pricing.
Inputs
The model you are running in production today.
The model you want to migrate to.
Average prompt size per API call — system prompt + context + user message. Simple chat: 500–2,000 · RAG chatbot: 2,000–8,000 · document analysis: 10,000–100,000 tokens.
Average completion length. Short answer: 200–500 · paragraph: 500–1,000 · long-form: 1,000–4,000 tokens.
Total API calls per month across all users and jobs.
Applies the same cache setting to both models for an apples-to-apples comparison.
Time to update prompts, run evals, handle edge cases, and deploy. Typical range: 20–120h.
Blended fully-loaded rate for your engineering team.
Extra cost multiplier for potential quality issues (re-evals, prompt tuning). 0.1 = 10% buffer.
Cost breakdown
| Item | Monthly | Yearly |
|---|---|---|
| GPT-5 — monthly | $812.50 | $9,750.00 |
| GPT-5 Mini — monthly | $162.50 | $1,950.00 |
| Monthly saving | $650.00 | $7,800.00 |
| Engineering cost (one-time) | $0.00 | $6,000.00 |
| Risk buffer (10%) | $0.00 | $600.00 |
| Total migration cost | $0.00 | $6,600.00 |
Comparison
| Option | Monthly | Yearly |
|---|---|---|
| Current: GPT-5current | $812.50 | $9,750.00 |
| Target: GPT-5 Minicheapest | $162.50 | $1,950.00 |
| Engineering cost (one-time) | $0.00 | $6,600.00 |
| 12-month net saving | $650.00 | $1,200.00 |
Pricing sources
Last verified 2026-06-30 · openai.com/api/pricing openai.com/api/pricing · platform.claude.com/docs/about-claude/pricing platform.claude.com/docs/about-claude/pricing · ai.google.dev/gemini-api/docs/pricing ai.google.dev/gemini-api/docs/pricing
Trends & comparison
Trend
Comparison (monthly vs. yearly)
When switching LLM models makes financial sense
Model migration makes economic sense when annual savings exceed migration cost within 6–12 months. For high-volume workloads on premium models, payback is often under 3 months. The key inputs: monthly request volume (determines savings magnitude), engineering hours (determines migration cost), and quality requirements (determines acceptable quality risk).
Quality risk: the factor most teams underestimate
The hidden cost of LLM migration is quality degradation. Cheaper models often need more explicit prompting, longer instructions, and more structured output schemas. Budget for prompt refinement (typically 40–60% of migration effort), structured evals on real production examples, and a monitoring period post-migration. A 10% quality risk buffer is conservative for most migrations; use 20%+ for complex agentic systems.
Frequently asked questions
Is switching from GPT-5 to GPT-5 Mini worth it?▾
In most cases, yes. GPT-5 Mini is 80% cheaper ($0.25/$2.00 vs $1.25/$10.00 per MTok). At 50,000 requests/month with 2,000 input + 500 output tokens, you save roughly $2,800/month ($33,600/year). With 40 engineering hours at $150/h = $6,000 migration cost, payback is just 2 months. Quality is typically 85–95% comparable — always run evals on your specific use case first.
How long does LLM model migration take?▾
A typical migration from GPT-5 to GPT-5 Mini takes 20–80 engineering hours depending on complexity: 5–10h for prompt review and initial testing, 10–20h for eval setup and quality measurement, 5–10h for edge case handling and prompt refinement, 5–10h for staged rollout and monitoring. High-complexity applications (multi-step agents, structured outputs) take longer.
What is the ROI of migrating from Claude Sonnet to Haiku?▾
Claude Haiku 4.5 is 67% cheaper than Sonnet 4.6 ($1.00/$5.00 vs $3.00/$15.00 per MTok). At 50,000 requests/month with 2,000 input + 500 output tokens, monthly saving is roughly $1,375. With 30 engineering hours at $150/h = $4,500 migration cost, payback is 3 months.
How do I account for quality risk when planning a model migration?▾
Use a quality risk buffer of 10–20% of direct engineering cost. This covers: prompt adjustments (cheaper models often need more explicit instructions), extended eval periods, potential rollback, and customer-facing quality monitoring. The quality risk factor in this calculator adds that buffer to your total migration cost.