Simulating realistic RAG / search-augmented answers parameters (8,000 in / 500 out with 50% cache reuse). Claude Sonnet 5 delivers a 6% cost reduction over GPT-5.3 Codex.
Quick answer
For RAG / search-augmented answers, Claude Sonnet 5 is the lower-cost option at $0.0138 per request versus $0.0147 for GPT-5.3 Codex, a modeled saving of 6%.
Method & trust
The comparison uses 8,000 input tokens, 500 output tokens, and 50% cache reuse for the selected workload. Pricing is applied per model, then scaled to monthly request volumes.
| Traffic Volume Tier | GPT-5.3 Codex Monthly | Claude Sonnet 5 Monthly | Monthly Savings by picking Claude Sonnet 5 |
|---|---|---|---|
| 1,000 reqs/mo (Dev/Testing) | $14.70 | $13.80 | Save $0.90 / mo |
| 10,000 reqs/mo (Small App) | $147.00 | $138.00 | Save $9.00 / mo |
| 100,000 reqs/mo (Growth Production) | $1,470.00 | $1,380.00 | Save $90.00 / mo |
| 1,000,000 reqs/mo (Scale SaaS) | $14,700.00 | $13,800.00 | Save $900.00 / mo |
Claude Sonnet 5 is 6% cheaper for RAG / search-augmented answers workloads. At standard RAG / search-augmented answers parameter ratios (8,000 input tokens, 500 output tokens, 50% cache hit), Claude Sonnet 5 costs $0.0138 per request compared to $0.0147 on GPT-5.3 Codex.
GPT-5.3 Codex offers a context window of 256,000 tokens (max output: 64,000), while Claude Sonnet 5 offers 1,000,000 tokens (max output: 128,000).
At 100,000 requests per month, using Claude Sonnet 5 saves $90.00 every month (or $1,080.00 annually) compared to GPT-5.3 Codex.
retrieved-context dominates cost — tune top-k and chunk size before switching models. Re-rank and drop marginal chunks; halving context roughly halves input cost. Deduplicate repeated chunks across queries to raise the cache hit rate.