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ModelCap

GPT-5.2

Arena #107No linked weights

OpenAI·#109 of 504 in the all-versions archive

GPT-5.2 is a language model from OpenAI. It ranks #109 of 504 in ModelCap's all-versions archive, with an Index score of 66.0, measured on 3 public benchmarks. Its score range of 61.3–70.7 spans positions #86–#135. It is listed at $1.75 per million input tokens and $14.00 per million output tokens across 2 providers. It reads up to 400K tokens of context, with no downloadable weights linked in the current source data.

Figures as of 6 Nov 2026, 13:52 UTC · download the public dataset · methodology

ModelCap Index · All-versions archive
66.0#109
Measured on 3 public benchmarks · range 61.3–70.7
Evidence as of 4 Nov 2026, 23:07 UTC
Market Gravity
43.8Increased by 0.2
Secondary market signal

Superseded by GPT-5.5. It no longer holds a current-board position; its all-versions archive rank is #109.

Input
$1.75
per 1M tokens
Output
$14.00
per 1M tokens
Context
400K
tokens
Providers
2
4 endpoints

Providers

Uptime measured over the last 30 minutes
ProviderInputOutputContextQuantUptime
OpenAIflexCheapest$0.875$7.00400K——
Azure$1.75$14.00400K—100.0%
OpenAI$1.75$14.00400K—100.0%
OpenAIfast$3.50$28.00400K——

Reasoning efforts

Best supported result can inform ModelCap

Published Max, X-High, High and other configurations for this model. These are sourced scores, not head-to-head essays.

Related community configurations

Human preference rating
ConfigurationRatingSource rankVotesSource
High
GPT-5.2 (High)
1437
CI 1434–1441
#10250KLMArena
Match 100%

Other versions (6)

ModelCap Index · All-versions archive

Methodology
66.0
Measured on 3 public benchmarks
All-versions archive
#109 of 504
Score range
61.3–70.7
Rank range
#86–#135
Evidence as of
4 Nov 2026, 23:07 UTC
Benchmarks used
ARC-AGI-2 Verified, Arena Coding, Arena Overall
Technical details
Public rank basis
Measured (measured)
Evidence label
Measured · 3 public benchmark observations across 3 boards
Index support
65.7% · strong
Identity binding
Exact catalogue product · openai/openai/gpt-5.2 · aggregates disclosed benchmark configurations · endpoint configuration not claimed
Index observations used
3
Qualified Index evidence point
66.0
Bayesian Evidence Score · measured evidence input only

BES normalizes admitted public benchmark evidence for measured Index rows. Its legacy score and observables prior do not define the public language rank.

Observed capability
66.0
Evidence status
confirmed · 87% mass
General preference
66.6
Coding
67.4
Agents & tools
—
Reasoning
44.8
Evidence breadth
95%
Evidence coverage
66%
Market and catalogue signals · secondary, never the language Index rank
Usage (OpenRouter popularity)
18.9
Liquidity (providers × uptime)
98.1
Open reach (HF downloads)
—
Surface (context / tools / modalities)
93.3
Freshness
28.4
  • · OpenRouter popularity #113
  • · 2 live providers
  • · Catalogue: context 400000, reasoning, tools, modalities File/Image/Text
  • · First seen 2025-12-10

These adoption and deployment observations remain context only. They do not change this model's ModelCap Index score or rank.

BES evidence selected · measured input only

The bounded 0–100 capability score blends each source’s competitive placement with its published achievement, then combines capability families. Evidence breadth adds a modest uncertainty adjustment; price and popularity are not part of benchmark-led rank.

Deployment readiness

Metadata index
48.5
partial · 56% metadata coverage
Not capability
Artifact reproducibility
0.0
Access & legal clarity
30.3
Deployability
90.0
Evaluation provenance
77.1

Not yet published: a pinned repository revision, the architecture and model type, a parameter count, safetensors weight metadata, the base model it derives from, a declared licence, a link to the licence terms, pinned evaluation dataset versions.

A metadata completeness and deployability index—not a safety certification, quality grade, or production-readiness claim.

Market activity

Venue coverage
Market Gravity
43.8
OpenRouter weekly popularity
#113 of 339

Market Gravity uses OpenRouter’s full-catalogue popularity order. Sparse Vercel top-ten observations appear only when published and do not affect the score.

Arena preference

Status
Ranked
Source
LMArena
Official rank
#107 of 419
Rating
1435.6
95% confidence interval
1432–1439
Votes
84K
Source published at
28 Oct 2026, 00:00 UTC
Category
overall
Identity match confidence
100%

Market Gravity breakdown

Usage55%
18.9

OpenRouter weekly popularity across the full model catalogue.

Liquidity25%
98.1

Independent providers versus the model's open or closed cohort, weighted by uptime.

Open reach15%
50.0

Hugging Face 30-day downloads for open models; neutral for closed models.

Freshness5%
28.4

Time since first public availability, on a six-month half-life.

Specification

Model ID
openai/gpt-5.2
Context window
400K tokens
Declared output cap
128K tokens

OpenRouter catalogue or provider-endpoint declaration. Limits can vary by provider and prompt length; a model-wide maximum has not been independently verified. OpenRouter metadata

Inputs
File, Image, Text
Outputs
Text
Tokenizer
GPT
Cached input tokens
$0.175 / 1M
First seen on OpenRouter
10 Dec 2025

Capabilities

  • Supported: Reasoning
  • Supported: Tool use
  • Supported: Structured output
  • Supported: Response format
  • Supported: Moderated

Benchmark leaderboards featuring GPT-5.2

All leaderboards
Public benchmark boards on which GPT-5.2 has a published result
LeaderboardScoreSource rankConfigurationPublished
Arena text leaderboardArena (LMArena)14371434–1441#102 of 419High28 Oct 2026
Arena coding leaderboardArena (LMArena)14891483–1495#99 of 414High28 Oct 2026
ARC-AGI-2 leaderboardARC Prize Foundation52.9%#104 of 280X-High4 Nov 2026
SWE-bench leaderboardSWE-bench (Princeton / SWE-agent team)72.8%#7 of 47High17 Feb 2026

GPT-5.2: common questions

How does GPT-5.2 rank among AI models?

GPT-5.2 is a superseded version and is not on the current board as of 6 November 2026. Its archive position, where one exists, is shown on the page; the newer version carries the current rank.

How much does GPT-5.2 cost per 1M tokens?

GPT-5.2 is listed at $1.75 per 1M input tokens and $14.00 per 1M output tokens as of 6 November 2026; the lowest output price among 2 providers is $7.00 on OpenAI. Prices come from the OpenRouter catalogue and re-observe on every refresh. For 1,000 requests using 2,000 input and 500 output tokens each, the listed rates imply $10.50 total (2M input + 0.5M output). This excludes caching, batch discounts, prompt-length tiers, tool charges and retries; verify the chosen endpoint's rate and limits before budgeting.

What is the context window of GPT-5.2?

GPT-5.2 has a published context window of 400K tokens (400,000). The snapshot lists a 128,000 token catalogue-declared route output cap. OpenRouter catalogue or provider-endpoint declaration. Limits can vary by provider and prompt length; a model-wide maximum has not been independently verified. The providers table lists each endpoint's context limit.

Is GPT-5.2 open-weight?

No linked weights. No downloadable model weights are linked in the current source data. This does not identify every API or chat product that offers the model.

Which API providers serve GPT-5.2?

2 providers serve GPT-5.2 through OpenRouter as of 6 November 2026: OpenAI and Azure. Each provider's price, context limit, quantization and measured uptime are in the providers table above.

Which benchmarks has GPT-5.2 been evaluated on?

GPT-5.2 has published results on 4 public boards tracked by ModelCap as of 6 November 2026: Arena text 1437 (#102 of 419), Arena coding 1489 (#99 of 414), ARC-AGI-2 52.9% (#104 of 280) and SWE-bench 72.8% (#7 of 47). Each board page ranks every tracked model on that benchmark. The ModelCap Index scores the results its methodology admits, with published uncertainty, and shows reference boards without scoring them.

When was GPT-5.2 released?

GPT-5.2 first appeared in the catalogue on 10 Dec 2025. It has since been superseded by GPT-5.5. Rank and price movements since then are recorded on the site's changes feed.