What kinds of workloads should you compare with gpt-5.2?

Compare routine and difficult requests separately, including reasoning, coding, structured analysis, and tool calls that reflect your production workload.

How should you evaluate gpt-5.2 before production?

Use representative tasks and compare quality, latency, token use, and relevant tool behavior with your current model. Use measured quality, latency, token use, and tool behavior to decide whether gpt-5.2 should become a general-purpose routing candidate.

How much does prompt caching save on gpt-5.2?

gpt-5.2 supports prompt caching, which can significantly reduce costs for repeated prompts with shared prefixes. The cache read price is substantially lower than the standard input price. Check the current pricing page for the exact cache hit discount ratio for gpt-5.2.

Can you call gpt-5.2 with the SDK you already use?

Yes. gpt-5.2 is compatible with the standard SDK. Set the model parameter to gpt-5.2 and use your MixRoute API key. If your current code already calls the compatible API, changing the base URL and model ID is typically all that is needed.

How should you begin a pilot with gpt-5.2?

Use measured quality, latency, token use, and tool behavior to decide whether gpt-5.2 should become a general-purpose routing candidate.

How do you get a cache hit on gpt-5.2?

To get a cache hit on gpt-5.2, send requests with identical prompt prefixes. The cache is keyed by the beginning of your prompt; as long as the prefix matches a previous request, subsequent calls benefit from the lower cached rate. Keep system messages and initial context consistent across calls for best results.

Does gpt-5.2 charge more for long inputs?

GPT-5.2 uses a single published rate for input, regardless of request length; see the pricing table for the applicable amount.

Model detail

GPT-5.2

Provided by OpenAI

Pay-as-you-go

GPT-5.2 is the latest frontier-grade model in the GPT-5 series, offering stronger agentic and long context perfomance compared to GPT-5.1. It uses adaptive reasoning to allocate computation dynamically, responding quickly to simple queries while spending more depth on complex tasks. Built for broad task coverage, GPT-5.2 delivers consistent gains across math, coding, sciende, and tool calling workloads, with more coherent long-form answers and improved tool-use reliability.

Model specs

Model ID: gpt-5.2

Context length: 400K
Max output: 128K
I/O modalities
Released: 2025-12

API endpoints

One MixRoute gateway, OpenAI-compatible

OpenAI-compatible /v1/chat/completions POST

Pricing

Flat rate, unit: /1M Tokens

Input

$1.7500 /1M Tokens

Completion

$14.0000 /1M Tokens

Selection summary

Quickly judge whether it fits your workload

What is this model good for?

Flagship model for complex reasoning and agentic workflows

GPT-5.2: GPT-5.2 is our previous flagship model for complex professional work. We recommend using the latest GPT-6 Astra. Learn more on the Model guidance page. Reasoning.effort supports: n. 400,000-token context.

What should you check before using it?

400,000 context, 128,000 output

OpenAI model. Supports tool calling, structured outputs, function calling. Knowledge cutoff: 2025-08-31.

Why use it through MixRoute?

Drop-in via OpenAI-compatible endpoint on MixRoute

Set the model parameter to "gpt-5.2" and use your MixRoute API key.

Capabilities & compatibility

Unconfirmed capabilities stay "Unknown," no guesses

Tool calling

GPT-5.2 supports function and tool calls.

EX Send a tools definition; the response returns tool_calls to execute and feed results back.

Structured output

GPT-5.2 can produce JSON-formatted output on demand.

EX response_format: { type: "json_schema" } forces valid JSON output.

Streaming

GPT-5.2 supports streamed responses.

EX stream: true streams tokens incrementally, so chat UIs render as they arrive.

Prompt caching

GPT-5.2 supports prompt caching under supported routing conditions.

EX Keep the system prompt and tool definitions at the start of the request; repeated prefixes are automatically billed at the cache-read rate.

Vision input

GPT-5.2 can process image inputs alongside text.

EX Pass a base64-encoded image in a image_url content part alongside text messages.

OpenAI SDK

Call GPT-5.2 through MixRoute's OpenAI-compatible endpoint.

EX Change base_url to https://api.mixroute.ai/v1; everything else follows the OpenAI style.

Token cost estimator

Live estimate from this page's pricing, not an actual bill

Input tokens Max per request 400K

Output tokens Max per request 128K

Requests / month

Cache hit rate –

This model has no cache-read price; caching is not counted

FAQ

Compare gpt-5.2 against models of similar capability and pricing on your actual workload. Evaluate latency, output quality, instruction following, and cost per task. Run side-by-side tests with your own prompts — the best model depends on your specific use case, not just benchmark scores.

Get started

01

Create an API key

Generate a key in the Console; one key calls every model.
02

Set the base URL

Fully OpenAI SDK-compatible; just swap the URL to connect.

https://api.mixroute.ai/v1
03

Specify the model ID

In the request's model field, enter:

gpt-5.2

Create an API key

New users get $5 in free credits

Test this model and alternate routes with the same request format

Start from a real workload, then let quality, total cost, and failure conditions decide whether to send production traffic.

Create an API key View integration docs