Cache-aware math
Cached input pricing comparison
RAG and agent apps reuse long prompts — cached-input pricing often matters more than output rates. Adjust the cache slider to see which models reward retrieval-heavy workloads.
Calculate my API costRelated: Llm Pricing For Rag · Ai Api Cost Per Month
Calculator
Start with your workload
Step 1
Review your assumptions
These are estimates, not measured usage. Edit the inputs or choose a preset.
Edit assumptions · 1,000 requests/month · 1,000 tokens/request · 75% input · 65% of input cached
1K requests / mo
1K tokens avg
Per request: 750 in · 250 out · 488 cached
Step 2
Lowest estimated cost
Top 5 models for this workload (unreviewed and conditional tariffs excluded)
General intelligence is not a task-specific quality guarantee. Test shortlisted models on your own examples. Source reviewed — exact offer checked on its provider page. Needs review — missing, stale or conflicting evidence; excluded from default recommendations. Estimates cover input/cache-read/output tokens only. Cache writes, storage, tools, search fees, taxes and unconfigured billing conditions are additional. Include billed reasoning tokens in your output estimate.
Selected model: cost breakdown
Estimate
Lowest estimated cost
AWS Bedrock · Amazon Nova Micro (standard)
From monthly cost (USD)
From $0.05
Based on: 1K requests · 750 input tokens/request · 250 output tokens/request · 65% of input from cache
Token costs only. Tool calls, search, storage, regional pricing, commitment discounts, and taxes may be excluded.
Explore all priced models
Step 3
All priced models
Jump to any of 62 models for this workload
Pick a model to focus the estimate above, or browse the ranked list.
How costs are calculated
Prices from ai-provider-pricing-validated.json, validated Thursday 8th October 2026. Confirm on official provider pages before billing decisions. Dataset contains 95 offer records, including archived entries and offers that require additional billing inputs or price evidence. Only reviewed offers appear in this calculator. See excluded offers and reasons
Model Cost Comparison · Built by Lazige · Methodology
How we calculate cost
Monthly estimate = (input tokens × input $/MTok) + (cached tokens × cached $/MTok when published) + (output tokens × output $/MTok), scaled to your message volume. See the methodology for validation sources and update cadence.
Topic scenarios
Cached input pricing comparison
RAG and agent apps reuse long prompts — cached-input pricing often matters more than output rates. Adjust the cache slider to see which models reward retrieval-heavy workloads.
“Start with a preset that matches product shape, then adjust volume after a week of real traffic.”
“Compare supported cache scenarios for RAG and agents, then validate the assumptions against actual usage.”
“Use the ranked list to shortlist two to three models, then validate quality on your eval set.”
“Re-run when traffic grows or vendors publish new tiers; check the dataset validation date and official rates.”