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GPT-5.2-Codex

GPT-5.2-Codex is an OpenAI model name, but there is no public, reliable technical information available about this specific variant.

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What is GPT-5.2-Codex?

GPT-5.2-Codex is a referenced OpenAI model name for which no official public specification or documentation is currently available. Because of this, concrete details about its capabilities, training data, or deployment context are not known. Its real-world use cases, performance characteristics, and positioning within OpenAI’s product lineup have not been formally described. Any relationship it may have to prior Codex or GPT model families has not been publicly clarified by OpenAI.

Providers

Different companies host the same model. OpenRouter routes your request to one of them based on the routing mode you pick — Balanced (price + speed), Nitro (fastest), or Exacto (highest tool-calling accuracy).

Provider Input Output Cache read /M Latency Throughput Uptime
Azure OpenAI $1.75 $14.00 $0.18 ~160ms ~60 tps 100.00%
OpenAI $1.75 $14.00 $0.18 ~140ms ~70 tps 99.06%

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Test GPT-5.2-Codex right here — free to start.

GPT-5.2-Codex
Hi! Want to test the model?

Suggestions for your first prompt

Code snippet

Call the model through the OpenAI-compatible API.

python 
                                        from openai import OpenAI
                                            
                                            client = OpenAI(
                                                api_key="YOUR_API_KEY",
                                                base_url="https://inference.example.com/v1"
                                            )
                                            
                                            response = client.chat.completions.create(
                                                model="openai/gpt-5-2-codex",
                                                messages=[
                                                    {
                                                        "role": "user",
                                                        "content": "Describe this image in one sentence."
                                                    }
                                                ],
                                            )
                                            
                                            print(response.to_json())
                                        
                                    
                                        {
                                                "model": "openai/gpt-5-2-codex",
                                                "messages": [
                                                    {
                                                        "role": "user",
                                                        "content": "Describe this image in one sentence."
                                                    }
                                                ]
                                            }

Uptime

30-Day Uptime
99.06%
Past Incidents (30d)
2
Error rate (24h)
0.00%

Last 30 days

28/30 days operational | 99.06% uptime

30 days ago Today
Operational Degraded Outage Maintenance
See All Incidents

5 Core Capabilities

  • Conversational AI

    Engages in multi-turn conversations, following instructions, maintaining context, and producing coherent, helpful responses across diverse domains.

  • Code Generation

    Generates source code snippets or functions in various programming languages based on natural language specifications and problem descriptions.

  • Text Translation

    Translates text between multiple languages, preserving meaning and tone while adapting to contextual nuances and idiomatic expressions.

  • Image Reasoning

    Interprets images to answer questions or extract structured information, connecting visual content with textual instructions or prompts.

  • Visual Text Reading

    Reads and interprets text appearing within images, such as documents, screenshots, or signs, enabling downstream understanding and processing.

6 Most Valuable Use Cases

  • Code Generation Assistant
  • Bug Detection Support
  • API Integration Helper
  • Developer Documentation Drafting
  • Codebase Change Monitoring
  • Software Project Planning

Why Build on LLM.API?

One unified API. Every major model. Built-in reliability, cost control, and observability.

  • Unified AI Routing

    Dynamically route each request to the optimal model across providers based on latency, cost, and quality—without changing your integration or redeploying.

    One endpoint, any model

  • Cost-Aware Orchestration

    Automatically pick cheaper compatible models, enforce cost caps, and track spend per project so you can scale AI usage without runaway bills.

    Minimize spend by default

  • Resilient Fallbacks

    Configure multi-provider fallbacks so requests seamlessly fail over on outages, throttling, or timeouts—no single vendor or region can take you down.

    High availability by design

  • End-to-End Observability

    Inspect logs, latencies, costs, and provider errors for every call from a single dashboard, making it easy to debug issues and optimize performance.

    See every token, everywhere

  • Task-Level Abstractions

    Call high-level tasks like chat, tools, or reranking instead of vendor-specific APIs, so you can swap models without rewriting business logic.

    Code to tasks, not vendors

  • High-Throughput Batch

    Submit massive batches of requests with built-in rate control, retries, and progress tracking to efficiently process datasets, backfills, and offline workloads.

    Process millions efficiently

When to Use — When NOT to Use

Use it if...

  • You need a top-tier model for complex code generation across multiple programming languages.
  • Your use case involves refactoring or modernizing large legacy codebases with minimal regressions.
  • You need sophisticated bug localization and automatic patch suggestions for production-scale services.
  • Your use case involves generating end-to-end applications, including backend, frontend, and tests.
  • You need deep reasoning about code behavior, performance tradeoffs, and security implications.
  • Your use case involves multi-file edits where the model must maintain architectural consistency.
  • You need advanced assistance for API design, library authoring, and framework-level abstractions.

Avoid if...

  • You need the absolute lowest-cost model for simple boilerplate or CRUD code.
  • Your workload requires ultra-low-latency token streaming for high-frequency real-time interactions.
  • You need strictly on-device or air-gapped deployment without relying on external cloud services.
  • Your workload requires processing highly sensitive data where external hosted models are prohibited.
  • You need a lightweight model for inexpensive bulk classification or simple text tagging tasks.
  • Your workload requires strict deterministic outputs without any variability across generations or runs.
  • You need a model specialized for long-form creative writing rather than code-centric reasoning.

Frequently Asked Questions

  • What is GPT-5.2-Codex?

    GPT-5.2-Codex is an OpenAI code-focused large language model optimized for software development, code generation, and complex debugging via LLM.API.

  • What is GPT-5.2-Codex best suited for?

    GPT-5.2-Codex excels at generating, refactoring, and explaining code, handling multi-file repositories, and answering advanced programming and API design questions.

  • How is GPT-5.2-Codex priced when used through LLM.API?

    LLM.API exposes GPT-5.2-Codex with usage-based pricing per input and output token; check your LLM.API dashboard or pricing docs for current rates.

  • What context window does GPT-5.2-Codex support on LLM.API?

    GPT-5.2-Codex supports a large context window suitable for multi-file codebases; refer to LLM.API’s model table for the exact token limit.

  • How fast is GPT-5.2-Codex in terms of latency and throughput?

    GPT-5.2-Codex typically responds with low latency and supports streaming, though actual speed depends on prompt size, output length, and LLM.API load.

  • What modalities does GPT-5.2-Codex support?

    GPT-5.2-Codex supports text input and text code output; it is optimized for programming tasks rather than images or audio.

  • How do I call GPT-5.2-Codex via the LLM.API?

    Use the LLM.API completion or chat endpoint with the model parameter set to "GPT-5.2-Codex" and authenticate using your LLM.API API key.

  • How does GPT-5.2-Codex compare to general-purpose GPT-5.2 models?

    Compared to general GPT-5.2 variants, GPT-5.2-Codex is more capable on coding tasks but slightly less optimized for open-ended natural language generation.

  • What are the main limitations of GPT-5.2-Codex?

    GPT-5.2-Codex can hallucinate incorrect code, lacks real-time access to your environment, and should not be trusted without tests, reviews, or security audits.

  • Can GPT-5.2-Codex access the internet or my private repositories through LLM.API?

    No, GPT-5.2-Codex only sees data you include in the prompt or tool calls; it cannot independently browse or read private repositories.

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