Pairwise benchmark snapshot · Aug 17, 2026noindex (thin pair)

Claude 3 Opus vs OpenAI: GPT-5.2-Codex benchmark

Name: Claude 3 Opus vs OpenAI: GPT-5.2-Codex AI benchmark comparison
Creator: CompareLLM
License: https://creativecommons.org/licenses/by/4.0/

This page compares Claude 3 Opus (Anthropic) and OpenAI: GPT-5.2-Codex (OpenAI) using the latest snapshots we have as of Aug 17, 2026. OpenAI: GPT-5.2-Codex wins on output price at $14/1M. OpenAI: GPT-5.2-Codex has the larger context window (400k tokens). Every cell below is a dated snapshot from a named public source — we do not invent missing scores, and we do not run SWE-bench ourselves.

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Anthropic

Claude 3 Opus

Original Claude 3 flagship. Kept so opus 3 vs later Opus and vs GPT-4o still resolve.

Elo 1,248$75/1M out

OpenAI

OpenAI: GPT-5.2-Codex

Auto-discovered from OpenRouter (openai/gpt-5.2-codex). Preview until a second source matches.

$14/1M out

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Model A

Model B

Quick vs:vs Claude Opus 4.5 vs Claude Opus 4.6 vs Claude Sonnet 4.5 vs Claude 3.7 Sonnet

Interactive Comparison Diagram

Matchup Breakdown

Tug-of-War Matchup Matrix

Category wins across intelligence, speed, and pricing efficiency.

Claude 3 Opus (6)vsOpenAI: GPT-5.2-Codex (3)

Claude 3 Opus: 6W (67%)Overall: Claude 3 OpusOpenAI: GPT-5.2-Codex: 3W (33%)

← Claude 3 OpusOpenAI: GPT-5.2-Codex →

Claude 3 Opus (4/5)

Intelligence & Reasoning

Preference Elo, Coding proficiency, SWE-bench & LiveBench accuracy

Preference Elo

1,248vs—

Coding Elo

—vs—

SWE-bench

38.4%vs—

LiveBench

46.2%vs—

GPQA Diamond

50.4%vs—

Claude 3 Opus: 4WOpenAI: GPT-5.2-Codex: 0W

Claude 3 Opus (2/2)

Speed & Latency

Generation throughput and time to first token responsiveness

Output speed

48 tok/svs—

Time to first token

420 msvs—

Claude 3 Opus: 2WOpenAI: GPT-5.2-Codex: 0W

OpenAI: GPT-5.2-Codex (3/3)

Pricing & Capacity

Cost per million tokens and max context window length

Output price

$75/1Mvs$14/1M

Input price

$15/1Mvs$1.75/1M

Context window

200kvs400k

Claude 3 Opus: 0WOpenAI: GPT-5.2-Codex: 3W

Capability Matchup Radar

Multi-Dimensional Capability Radar

Each spoke is a skill. Farther from the center is better (0–100th percentile). Tap any dot to inspect details.

Tap any node to inspect

Percentile 0–100

Dimensional AdvantageClaude 3 Opus 4/6

Preference Elo

No shared data

Throughput Speed

No shared data

Price Efficiency

OpenAI: GPT-5.2-Codex

$61.00/1M cheaper

Full Benchmark Score Matrix

—

Elo

High is better

1,248

EloHigh is better

—

LiveBench

High is better

46.2%

LiveBenchHigh is better

—

SWE-bench

High is better

38.4%

SWE-benchHigh is better

—

GPQA

High is better

50.4%

GPQAHigh is better

—

TTFT

Low is better

420 ms

TTFTLow is better

—

Speed

High is better

48 tok/s

SpeedHigh is better

—

In $

Low is better

$15/1M

In $Low is better

$1.75/1M+757%

Out $

Low is better

$75/1M

Out $Low is better

$14/1M+436%

Context

High is better

200k

ContextHigh is better

400k+100%

Interactive Simulator

Workload Cost & Savings Calculator

Simulate monthly production API costs based on published $/1M tokens.

Save up to 84% with OpenAI: GPT-5.2-Codex

Monthly Volume50M tokens/mo

Quick Presets:

Token Ratio (In vs Out)70% In / 30% Out

RAG / Search (10% out)Coding / Chat (50% out)

Claude 3 Opus$1,650.00 / mo

In: $525.00Out: $1125.00

OpenAI: GPT-5.2-Codex$271.25 / mo

In: $61.25Out: $210.00

Estimated Cost Delta

OpenAI: GPT-5.2-Codex is estimated to save $1,378.75/month ($16,545/year).

Based on 50M tokens (30% gen)

Key Selection Recommendations

1
OpenAI: GPT-5.2-Codex:Pick OpenAI: GPT-5.2-Codex when you are optimizing output cost.

Recommended Workload Routing

Repo / coding agentsinsufficient data

Need SWE-bench on both sides.

High-volume chatOpenAI: GPT-5.2-Codex

Lower output list price ($14/1M).

Voice / low-latency UIinsufficient data

Need TTFT on both sides.

Long-document RAGOpenAI: GPT-5.2-Codex

Larger window (400k).

Screenshots / visionClaude 3 Opus

Claude 3 Opus is the side marked multimodal in the catalog.

Target Workload	Recommended Pick	Evaluation Rationale
Repo / coding agents	insufficient data	Need SWE-bench on both sides.
High-volume chat	OpenAI: GPT-5.2-Codex	Lower output list price ($14/1M).
Voice / low-latency UI	insufficient data	Need TTFT on both sides.
Long-document RAG	OpenAI: GPT-5.2-Codex	Larger window (400k).
Screenshots / vision	Claude 3 Opus	Claude 3 Opus is the side marked multimodal in the catalog.

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LIVE

Anthropic

Claude 3 Opus

Elo 1,248

LiveBench46.2%

SWE-bench38.4%

Speed48 tok/s

Output cost$75/1M

OpenAI

OpenAI: GPT-5.2-Codex

Elo n/a

LiveBench—

SWE-bench—

Speed—

Output cost$14/1M

Frequently Asked Questions

Which is better overall, Claude 3 Opus or OpenAI: GPT-5.2-Codex?: We do not have preference Elo for both models, so we do not declare an overall winner. Compare the metrics that exist.
Which is better at coding, Claude 3 Opus or OpenAI: GPT-5.2-Codex?: SWE-bench is missing for at least one model, so we do not rank coding from a single number.
Which is cheaper to run in production?: OpenAI: GPT-5.2-Codex output tokens are $14/1M versus $75/1M. Input prices and retry rates still move the real bill.
Which is faster, Claude 3 Opus or OpenAI: GPT-5.2-Codex?: We do not have TTFT for both models.
Which has the larger context window?: OpenAI: GPT-5.2-Codex accepts 400k tokens versus 200k.
Can I self-host either model?: Neither model is marked open-weights here. You are comparing hosted APIs.
Are these scores from CompareLLM’s own evals?: No. V1 aggregates public leaderboards (and optional first-party latency pings). Each cell names its source and date. Read /methodology.
What does preference Elo mean on this page?: Preference Elo is a crowd vote from LMArena / Arena. People see two hidden answers and pick the one they like more. The model that wins more often gets a higher Elo. That means people preferred it — not that it passed a school test. It is not SWE-bench, not accuracy, and not a number we invent. Claude 3 Opus and OpenAI: GPT-5.2-Codex Elo cells are dated snapshots from the named source — we do not compute Arena ourselves.

Similar Head-to-Head Comparisons

All Claude 3 Opus matchups →|All OpenAI: GPT-5.2-Codex matchups →

Claude 3 Opus vs Claude Opus 4 (next opus)Claude Opus 4.5 vs Claude 3 Opus Claude Opus 4.6 vs Claude 3 Opus Claude Sonnet 4.5 vs Claude 3 Opus GPT-5 vs Claude 3 Opus GPT-4.5 Orion vs Claude 3 Opus

Claude 3 Opus vs OpenAI: GPT-5.2-Codex benchmark

Interactive Comparison Diagram

Matchup Breakdown

Tug-of-War Matchup Matrix

Category wins across intelligence, speed, and pricing efficiency.

Claude 3 Opus (6)vsOpenAI: GPT-5.2-Codex (3)

Claude 3 Opus: 6W (67%)Overall: Claude 3 OpusOpenAI: GPT-5.2-Codex: 3W (33%)

← Claude 3 OpusOpenAI: GPT-5.2-Codex →

Claude 3 Opus (4/5)

Intelligence & Reasoning

Preference Elo, Coding proficiency, SWE-bench & LiveBench accuracy

Preference Elo

1,248vs—

Coding Elo

—vs—

SWE-bench

38.4%vs—

LiveBench

46.2%vs—

GPQA Diamond

50.4%vs—

Claude 3 Opus: 4WOpenAI: GPT-5.2-Codex: 0W

Claude 3 Opus (2/2)

Speed & Latency

Generation throughput and time to first token responsiveness

Output speed

48 tok/svs—

Time to first token

420 msvs—

Claude 3 Opus: 2WOpenAI: GPT-5.2-Codex: 0W

OpenAI: GPT-5.2-Codex (3/3)

Pricing & Capacity

Cost per million tokens and max context window length

Output price

$75/1Mvs$14/1M

Input price

$15/1Mvs$1.75/1M

Context window

200kvs400k

Claude 3 Opus: 0WOpenAI: GPT-5.2-Codex: 3W

Recommended Workload Routing

Repo / coding agentsinsufficient data

Need SWE-bench on both sides.

High-volume chatOpenAI: GPT-5.2-Codex

Lower output list price ($14/1M).

Voice / low-latency UIinsufficient data

Need TTFT on both sides.

Long-document RAGOpenAI: GPT-5.2-Codex

Larger window (400k).

Screenshots / visionClaude 3 Opus

Claude 3 Opus is the side marked multimodal in the catalog.

Target Workload	Recommended Pick	Evaluation Rationale
Repo / coding agents	insufficient data	Need SWE-bench on both sides.
High-volume chat	OpenAI: GPT-5.2-Codex	Lower output list price ($14/1M).
Voice / low-latency UI	insufficient data	Need TTFT on both sides.
Long-document RAG	OpenAI: GPT-5.2-Codex	Larger window (400k).
Screenshots / vision	Claude 3 Opus	Claude 3 Opus is the side marked multimodal in the catalog.

Frequently Asked Questions

Which is better overall, Claude 3 Opus or OpenAI: GPT-5.2-Codex?

We do not have preference Elo for both models, so we do not declare an overall winner. Compare the metrics that exist.

Which is better at coding, Claude 3 Opus or OpenAI: GPT-5.2-Codex?

SWE-bench is missing for at least one model, so we do not rank coding from a single number.

Which is cheaper to run in production?

OpenAI: GPT-5.2-Codex output tokens are $14/1M versus $75/1M. Input prices and retry rates still move the real bill.

Which is faster, Claude 3 Opus or OpenAI: GPT-5.2-Codex?

We do not have TTFT for both models.

Which has the larger context window?

OpenAI: GPT-5.2-Codex accepts 400k tokens versus 200k.

Can I self-host either model?

Neither model is marked open-weights here. You are comparing hosted APIs.

Are these scores from CompareLLM’s own evals?

No. V1 aggregates public leaderboards (and optional first-party latency pings). Each cell names its source and date. Read /methodology.

What does preference Elo mean on this page?

Preference Elo is a crowd vote from LMArena / Arena. People see two hidden answers and pick the one they like more. The model that wins more often gets a higher Elo. That means people preferred it — not that it passed a school test. It is not SWE-bench, not accuracy, and not a number we invent. Claude 3 Opus and OpenAI: GPT-5.2-Codex Elo cells are dated snapshots from the named source — we do not compute Arena ourselves.