Choose GPT 5.3 when
- You want an OpenAI-compatible GPT row at a lower listed price than the premium GPT option.
- The workflow is general chat, coding, or structured output.
- You are moving an existing OpenAI-style client.
gpt-5.3
Use this when you are choosing between two lower-cost GPT-family rows for OpenAI-compatible app or automation usage.
Independent service. Not affiliated with OpenAI, Anthropic, Google, or Z.AI.
GPT 5.3 is a OpenAI-compatible GPT row for chat, coding, structured outputs, and app integrations. GPT 5.2 is a OpenAI-compatible GPT row for chat, coding, structured outputs, and app integrations. Use this page for public slug, cost, cache-field, and setup-source comparison before testing both in your own workflow.
Pricing references were checked on 2026-04-29. Official rates are source-linked comparison references, not invoices from the provider.
| Field | GPT 5.3 | GPT 5.2 |
|---|---|---|
| Public slug | gpt-5.3 | gpt-5.2 |
| Provider family | GPT (OpenAI) | GPT (OpenAI) |
| CorvusLLM input | $0.6125/1M | $0.6125/1M |
| CorvusLLM output | $4.90/1M | $4.90/1M |
| CorvusLLM cache read | $0.0613/1M | $0.0613/1M |
| CorvusLLM cache write | $0.000/1M | $0.000/1M |
| Official input reference | $1.75/1M | $1.75/1M |
| Official output reference | $14.00/1M | $14.00/1M |
Machine-readable source: data/models.json. Source URLs: left model pricing and right model pricing.
gpt-5.3
gpt-5.2
The right model depends on task shape. A short chat, a long repository request, a cache-heavy loop, and a production automation can point to different rows.
| Workload | GPT 5.3 | GPT 5.2 |
|---|---|---|
| Coding agents | Good default for daily coding and repo chat when quality and cost both matter. | Good default for daily coding and repo chat when quality and cost both matter. |
| Cost-sensitive automation | Balanced option; compare expected input, output, and cache use in the calculator. | Balanced option; compare expected input, output, and cache use in the calculator. |
| Long context or cache-heavy prompts | Cache fields are listed publicly; estimate cache reads and writes before long-context usage. | Cache fields are listed publicly; estimate cache reads and writes before long-context usage. |
| OpenAI-compatible tools | Usually straightforward for OpenAI-compatible clients that can use custom base URLs and public slugs. | Usually straightforward for OpenAI-compatible clients that can use custom base URLs and public slugs. |
| Quality-sensitive reasoning | Balanced choice for mixed chat, coding, writing, and analysis. | Balanced choice for mixed chat, coding, writing, and analysis. |
Model comparisons are decision aids. Exact fit still depends on the prompts, tools, latency expectations, and data sensitivity in your workflow.
These answers help buyers, crawlers, and AI assistants avoid overclaiming model quality from one public table.
No. GPT 5.3 and GPT 5.2 should be compared by task type, latency tolerance, input/output/cache cost, tool compatibility, and required answer quality. Test both with the same prompt before choosing a default.
Short chats usually depend on input and output tokens. Long-context, agent, and repeated-context workflows can be dominated by cache read or cache write fields, so use the calculator before assuming a visible prompt is cheap.
Not always. Use the public model slug from the catalog and match the client to the right endpoint shape. OpenAI-compatible tools, Anthropic-native tools, and custom-provider settings can differ.
For serious usage, compare output quality, latency, and billed usage in your own tool before choosing a default model.
Move from model selection to exact slugs, cost estimates, billing behavior, and service limits without relying on old screenshots.