OpenAI: GPT-5.3-Codex API Pricing
OpenAI: GPT-5.3-Codex costs $1.75 per 1M input tokens and $14.00 per 1M output tokens (cache reads: $0.175). Context window: 400K. Prices verified 2026-10-21 · source
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From our own daily snapshot archive — independent of provider announcements.
Intelligence measures reasoning/knowledge/coding benchmarks. A high score with a low blended price = value pick; check the value chart to see where this model lands.
Token economics
| Token type | Price | vs base input |
|---|---|---|
| Standard input | $1.75 | — |
| Cache read | $0.175 | −90% |
| Output | $14.00 | — |
| Web search tool | $10/1k searches | — |
Prompt caching stores repeated context server-side: reads cost far less, but writes carry a one-time premium.
Higher effort = deeper thinking = more reasoning tokens billed as output.
What would OpenAI: GPT-5.3-Codex cost you per month?
| Workload | Requests/mo | Avg tokens (in/out) | Est. monthly cost |
|---|---|---|---|
| Light chatbot | 10,000 | 800 / 400 | $70.00 |
| Coding agent | 5,000 | 8,000 / 2,000 | $210.00 |
| RAG pipeline | 30,000 | 4,000 / 500 | $420.00 |
| Doc summarizer | 2,000 | 20,000 / 1,000 | $98.00 |
Estimates use list prices without prompt caching. Caching can cut input cost by up to 90% on repeated context.
About OpenAI: GPT-5.3-Codex
GPT-5.3-Codex is OpenAI’s most advanced agentic coding model, combining the frontier software engineering performance of GPT-5.2-Codex with the broader reasoning and professional knowledge capabilities of GPT-5.2. It achieves state-of-the-art results...
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Frequently asked questions
How much does OpenAI: GPT-5.3-Codex cost?
OpenAI: GPT-5.3-Codex costs $1.75 per 1M input tokens and $14.00 per 1M output tokens; cached input tokens cost $0.175 per 1M. Verified 2026-10-21 — provider source.
What is the context window?
400K tokens, with up to 128K output tokens per response. That's roughly 500 pages of text in a single request.
Does it support prompt caching?
Yes — cached input is $0.175/1M, about 90% cheaper than standard input. Agents and RAG workloads with repeated context benefit most.
What's a cheaper alternative?
ScaleDown: Summarize saves about 99% on a typical workload with comparable quality.
Official resources
- OpenAI: GPT-5.3-Codex on OpenRouter — live endpoint, pricing source of record.
- Artificial Analysis leaderboard → — independent intelligence and performance rankings.
- OpenAI pricing → — first-party pricing and billing details.
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