Singularity Logs

THE MODEL, IN DETAIL / OpenAI

gpt-5.2-codex

openai/gpt-5.2-codexProprietaryReasoning

GPT-5.2-Codex is an upgraded version of GPT-5.1-Codex optimized for software engineering and coding workflows. It is designed for both interactive development sessions and long, independent execution of complex engineering tasks....

OpenRouter
Source-linked model intelligenceCatalog added 14 Jan 2026Specifications observed 16 Oct 2026

Web development

#115

Arena rating

Context window

400K

128K max output tokens

Input price

$1.75

USD / million input tokens

Output price

$14

USD / million output tokens

Inference providers

1

1 provider routes observed

Measured output speed

—

No model-level measurement

01 / PERFORMANCE

A clearer view of capability.

Read the score, understand the context, and explore where this model sits among its peers.

Performance fingerprint

Individual published accuracy scores · not a composite index

At least three published accuracy scores are needed for this view.

In good company

Web development · Arena · official dataset

1,811.1
Anthropic
1,780.2
OpenAI
1,773.7
Anthropic
1,760.1
OpenAI
1,742.7
Anthropic
1,713
Anthropic
1,690
Anthropic
1,685.9
OpenAI
1,678
Google
1,673.2
alibaba

140 models in the source cohort. Showing selected nearby models. Evaluation settings can differ.

Evidence, by task.

Coverage is not a capability score.

0published results
0 evaluation sources
ReasoningAwaiting evidence
CodingAwaiting evidence
MathematicsAwaiting evidence
VisionAwaiting evidence
AgenticAwaiting evidence
Long contextAwaiting evidence

Documented features, task evaluations, and preference rankings describe different things. Missing coverage does not imply a model cannot perform a task.

Explore our methodology

Where people rank it

Published rankings for this exact model or configuration. Each source keeps its original metric.

Web developmentArena rating · 13 Oct 2026#1151,338.4Confidence interval: 1,329.5–1,347.3

02 / BENCHMARK EXPLORER

The numbers behind the model.

Original results, exact versions, and a direct path to the evidence behind every score.

0 published results

Percentage-based evaluations will appear here when published.

0 percentage-based evaluations. Each benchmark measures a different task; compare results within the same evaluation and protocol.

Artificial Analysis indices

Published in the OpenRouter catalog · source-defined index values

Intelligence Index28.5

Catalog observation: 16 Oct 2026. Index versions and evaluation settings are not supplied in this feed. These are not Singularity composite scores.

Artificial Analysis

Design Arena

Source-reported Elo across individual design categories

Androidnative1,176
agents arena · Rank #20 · 47.5% win rate
Fullstack993
agents arena · Rank #41 · 37.2% win rate
Godotgamedev1,142
agents arena · Rank #24 · 47.8% win rate
Mobileapps1,087
agents arena · Rank #40 · 46.6% win rate
Webapps1,044
agents arena · Rank #39 · 39.6% win rate

Catalog observation: 16 Oct 2026. Category ratings have separate comparison pools.

03 / COST & VALUE

Know what your workload costs.

Explore token prices, see where the spend goes, and model a workload of your own.

Input$1.75per million tokens
Output$14per million tokens
Cache read$0.175per million tokens
Cache write—per million tokens
Additional published rates
Additional rates supplied by the model catalog
Billing fieldPublished rateBilling basis
Web Search$0.01Source-supplied USD rate; see provider billing terms

Workload cost calculator

Change the numbers. See the trade-offs.

Token estimate only. Excludes cache writes, tools, and other provider fees. Actual token usage and provider limits vary.

Your estimated spend

1,000 requests · 11M tokens

$31.5estimated total
Uncached input$17.5
Cached input$0
Output$14
Per request$0.0315
Without cache discount$31.5
Estimated cache savings$0

04 / INFERENCE NETWORK

One model. Different ways to run it.

Compare inference routes by price, context, quantization, and reported availability.

1 providers · 1 routes
Provider routes for gpt-5.2-codex, observed 16 Oct 2026
Provider / routeInput / MOutput / MCache / MContextOutput limitSpeedLatencyAvailability · 1dRates
AAzureQuantization not disclosed$1.75$14$0.175400K128K——100%

Snapshot observed 16 Oct 2026. Speed and latency are the reported 30-minute median when available. This is a dated snapshot, not live monitoring.

Provider price comparison

USD per million tokens · input and output rates

InputOutput
Azure
Input
$1.75
Output
$14

Reported availability

Provider availability over the selected observation window

Azure100%

Output speed

Reported 30-minute p50 · tokens per second

No provider throughput measurements were returned in this snapshot.

Response latency

Reported 30-minute p50 · seconds

No provider latency measurements were returned in this snapshot.

Context by provider

Actual route limits can differ from the catalog maximum

Azure400K

05 / CAPABILITIES & MODALITIES

What goes in. What comes out.

A map of documented interfaces and API features, separate from benchmark performance.

INPUT MODALITIES

TextImage
gpt-5.2-codexReasoning supported

OUTPUT MODALITIES

Text

Feature support

Listed catalog API parameters and documented pricing features

ReasoningSupported
Tool callingSupported
Tool choiceSupported
Structured outputsSupported
Response formatSupported
Reasoning detailsSupported
Seed controlSupported
Stop sequencesNot listed
Prompt cachingSupported
TemperatureNot listed

Room to work

Context capacity and completion limits

400Ktotal context tokens
Context window
128Kmax output

Output tokens share the total context budget. The maximum completion length is a separate limit, and individual provider routes may have smaller limits.

Catalog context
400,000 tokens
Maximum output
128,000 tokens
Top-provider context
400,000 tokens

Features vary by route

Check the provider before depending on a specific API feature.

API feature support by provider
Provider routeReasoningToolsStructured outputResponse formatImplicit caching
AzureSupportedSupportedSupportedSupportedSupported

06 / UNDER THE HOOD

The complete specification sheet.

Exact identities, model architecture, limits, and the defaults that shape a request.

Identity & architecture

Developer
OpenAI
Exact identity
gpt-5.2-codex
Subject
Model Configuration
Access
proprietary
License
Proprietary
Parameters
Not disclosed
Tokenizer
GPT
Instruction format
Not disclosed

Reasoning & controls

Reasoning
Supported
Mandatory reasoning
Yes
Reasoning by default
Not documented
Published configuration
Not disclosed
Supported reasoning efforts
xhigh, high, medium, low
Default reasoning effort
medium
API parameters
10
Provider moderation
No
Quantization variants
Not disclosed

Dates & limits

Catalog added
14 Jan 2026
Knowledge cutoff
Not disclosed
Catalog expiration
Not documented
Specifications observed
16 Oct 2026
Providers observed
16 Oct 2026
Request limits
Provider-specific / not supplied
Canonical catalog ID
openai/gpt-5.2-codex-20260114

API parameters & defaults

Availability is catalog-wide. Defaults can vary across providers.

include_reasoningSupported · default not supplied
max_completion_tokensSupported · default not supplied
reasoningSupported · default not supplied
reasoning_effortSupported · default not supplied
response_formatSupported · default not supplied
seedSupported · default not supplied
structured_outputsSupported · default not supplied
tool_choiceSupported · default not supplied
toolsSupported · default not supplied
verbositySupported · default not supplied
top_pDefault setting
temperatureDefault setting
frequency_penaltyDefault setting

07 / BUILD WITH THIS MODEL

From exploration to your first request.

Use the documented catalog identifier and keep your API key in an environment variable.

Make an API request

const response = await fetch(
  "https://openrouter.ai/api/v1/chat/completions",
  {
    method: "POST",
    headers: {
      Authorization: `Bearer ${process.env.OPENROUTER_API_KEY}`,
      "Content-Type": "application/json",
    },
    body: JSON.stringify({
      "model": "openai/gpt-5.2-codex",
      "messages": [
        {
          "role": "user",
          "content": "Explain the trade-offs in this design."
        }
      ]
    }),
  },
);
if (!response.ok) throw new Error(`HTTP ${response.status}`);
const data = await response.json();
console.log(data.choices[0].message.content);

08 / PROVENANCE & HISTORY

Every number has a story.

Follow the source, check the observation date, and distinguish published results from model specifications.

The observation trail

Recorded events, in chronological order

Added to the model catalog

Catalog creation date, as recorded by OpenRouter.

Model specifications observed

Catalog pricing, limits, and supported parameters captured.

Provider routes observed

1 inference routes in this snapshot.

Observation dates describe when data was captured. They do not represent newly run evaluations or continuous performance monitoring.

Published observation ledger

Historical evidence, with source and version preserved.

No published benchmark observations for this selection. Published preference rankings appear separately above.

09 / A FEW MORE DETAILS

Questions worth asking.

Quick answers, drawn from this model’s connected specifications.

How much does gpt-5.2-codex cost?

Catalog starting rates are $1.75 per million input tokens and $14 per million output tokens. Cache-read pricing is $0.175 per million tokens. Compare provider routes and service tiers above for their specific prices.

How much context can it handle?

400,000 tokens in the catalog context window. The catalog lists a maximum of 128,000 completion tokens. Provider limits can differ.

Does it support tools and structured output?

Tool calling: listed as supported. Structured outputs: listed as supported. See the provider feature matrix for route-specific differences.

How should I interpret these benchmark results?

Read the benchmark name, exact version, metric, source, and model configuration together. Different evaluation settings can change the result. Preference ratings and source-defined composite indices remain separate from task accuracy.

Are these prices and provider measurements live?

This page uses dated source snapshots. Catalog data was observed on 16 Oct 2026. Provider routes were observed on 16 Oct 2026. Missing measurements are not estimated or treated as zero.

KEEP EXPLORING

More from OpenAI.

Explore related identities from the same developer, or take them into a side-by-side comparison.

THE RIGHT MODEL STARTS WITH THE RIGHT CONTEXT.

Put the details side by side.

Explore the trade-offs in a direct model comparison.

Compare gpt-5.2-codex
Source-backed evidence. Different tasks. A clearer picture.
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