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gpt-5.2-codex

OpenAI's most intelligent coding model optimized for long-horizon, agentic coding tasks.

VisionReasoningTool callingCachingWeb searchJSON schema
Try gpt-5.2-codexCompareDocs

Specifications

Context window400K tokens
Max output128K tokens
API typechat
AddedJan 22, 2026
Model IDazure/gpt-5.2-codex@eastus2
Data retentionNo
Used for trainingNo
Provider location🇺🇸 US / 🇪🇺 EU
Privacy policyMicrosoft Privacy Statement→

Benchmarks

Released 2025-12-11
Coding Indexcoding
43.0%

Artificial Analysis Coding Index — a composite of coding evaluations including LiveCodeBench, SciCode and Terminal-Bench.

GPQA Diamondreasoning
89.9%

Graduate-level physics, chemistry & biology questions designed to resist Googling.

Intelligence Indexreasoning
40.1%

Artificial Analysis Intelligence Index — a composite of multiple evaluations measuring overall model capability.

Scores are sourced from official model cards, Artificial Analysis, and public leaderboards. Benchmarks measure specific skills and do not capture every aspect of model quality. Always test on your own workload.

Pricing

Input / 1M
$1.75
Output / 1M
$14.00
Cache write
N/A
Cache read / 1M
$0.17
Estimated cost
100K input + 10K output$0.31
1M input + 100K output$3.15
10M input + 1M output$31.50

Requesty charges exactly what the upstream provider charges, no markup, no per-request fees. Prompt caching and smart routing can reduce effective cost by 30-80%.

Quickstart

Drop-in compatible with the OpenAI SDK. Change the base URL, swap in your Requesty API key, and set the model to azure/gpt-5.2-codex@eastus2.

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from openai import OpenAI

client = OpenAI(
    api_key="YOUR_REQUESTY_API_KEY",
    base_url="https://router.requesty.ai/v1",
)

response = client.chat.completions.create(
    model="azure/gpt-5.2-codex@eastus2",
    messages=[
        {"role": "user", "content": "Explain quantum computing in one paragraph."},
    ],
)

print(response.choices[0].message.content)

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Frequently asked questions

How much does gpt-5.2-codex cost?
gpt-5.2-codex is priced at $1.75 per million input tokens and $14.00 per million output tokens when accessed via Requesty. Prompt caching is supported, which can cut effective input cost by up to 90% on repeated context. Requesty charges exactly what the upstream provider charges, we don't add markup.
What is the context window of gpt-5.2-codex?
gpt-5.2-codex has a context window of 400K tokens, with a maximum output of 128K tokens per response. That's roughly 533 words of input you can fit in a single prompt.
How does gpt-5.2-codex perform on benchmarks?
gpt-5.2-codex scores 92.1% on τ²-Bench, 89.9% on GPQA Diamond, 54.6% on SciCode. See the full benchmark chart above for results across MMLU Pro, GPQA Diamond, SWE-Bench Verified, HumanEval, MATH, AIME, MMMU, and LiveBench.
What can gpt-5.2-codex do?
gpt-5.2-codex supports vision input, tool calling, extended reasoning, prompt caching, web search, structured outputs (JSON schema). You can call it through any OpenAI-compatible client by pointing base_url to Requesty.
How do I use gpt-5.2-codex with the OpenAI SDK?
Install the OpenAI SDK, set base_url to "https://router.requesty.ai/v1", set your API key to your Requesty key, and set the model to "azure/gpt-5.2-codex@eastus2". The Quickstart above shows Python, JavaScript and cURL snippets.
Can I run gpt-5.2-codex through Requesty?
Yes. gpt-5.2-codex runs through Requesty's OpenAI-compatible API, served from Microsoft Azure AI in eastus2. You do not host the model yourself: point base_url at Requesty, set the model to "azure/gpt-5.2-codex@eastus2", and requests are routed to the upstream provider with automatic failover. The same key gives you 400+ other models too.
What region is this deployment?
This variant of gpt-5.2-codex is deployed in eastus2. Region-specific endpoints matter for data residency, latency to your users, and compliance requirements (GDPR, HIPAA). Other regions for the same model may be listed on the Microsoft Azure AI provider page.

Access gpt-5.2-codex through Requesty

One API key, 400+ models, OpenAI-compatible. No markup on provider prices, automatic failover, and smart caching built-in.

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