Pairwise benchmark snapshot · Aug 16, 2026noindex (thin pair)

GLM-5.2 vs OpenAI: GPT-5.3-Codex benchmark

Name: GLM-5.2 vs OpenAI: GPT-5.3-Codex AI benchmark comparison
Creator: CompareLLM
License: https://creativecommons.org/licenses/by/4.0/

This page compares GLM-5.2 (Zhipu) and OpenAI: GPT-5.3-Codex (OpenAI) using the latest snapshots we have as of Aug 16, 2026. GLM-5.2 wins on output price at $0.97/1M. GLM-5.2 has the larger context window (1M 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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Zhipu

GLM-5.2

Zhipu flagship. Strong Chinese/English coding and agents.

Elo 1,492$0.9680000000000001/1M out

OpenAI

OpenAI: GPT-5.3-Codex

Auto-discovered from OpenRouter (openai/gpt-5.3-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.

GLM-5.2 (10)vsOpenAI: GPT-5.3-Codex (0)

GLM-5.2: 10W (100%)Overall: GLM-5.2OpenAI: GPT-5.3-Codex: 0W (0%)

← GLM-5.2OpenAI: GPT-5.3-Codex →

GLM-5.2 (5/5)

Intelligence & Reasoning

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

Preference Elo

1,492vs—

Coding Elo

1,504vs—

SWE-bench

69.3%vs—

LiveBench

65.2%vs—

GPQA Diamond

79.5%vs—

GLM-5.2: 5WOpenAI: GPT-5.3-Codex: 0W

GLM-5.2 (2/2)

Speed & Latency

Generation throughput and time to first token responsiveness

Output speed

84 tok/svs—

Time to first token

270 msvs—

GLM-5.2: 2WOpenAI: GPT-5.3-Codex: 0W

GLM-5.2 (3/3)

Pricing & Capacity

Cost per million tokens and max context window length

Output price

$0.97/1Mvs$14/1M

Input price

$0.31/1Mvs$1.75/1M

Context window

1Mvs400k

GLM-5.2: 3WOpenAI: GPT-5.3-Codex: 0W

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 AdvantageGLM-5.2 6/6

Preference Elo

No shared data

Throughput Speed

No shared data

Price Efficiency

GLM-5.2

$13.03/1M cheaper

Full Benchmark Score Matrix

—

Elo

High is better

1,492

EloHigh is better

—

Code Elo

High is better

1,504

Code EloHigh is better

—

LiveBench

High is better

65.2%

LiveBenchHigh is better

—

SWE-bench

High is better

69.3%

SWE-benchHigh is better

—

GPQA

High is better

79.5%

GPQAHigh is better

—

TTFT

Low is better

270 ms

TTFTLow is better

—

Speed

High is better

84 tok/s

SpeedHigh is better

—

In $

Low is better

+468%$0.31/1M

In $Low is better

$1.75/1M

Out $

Low is better

+1346%$0.97/1M

Out $Low is better

$14/1M

Context

High is better

+162%1M

ContextHigh is better

400k

Interactive Simulator

Workload Cost & Savings Calculator

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

Save up to 91% with GLM-5.2

Monthly Volume50M tokens/mo

Quick Presets:

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

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

GLM-5.2$25.30 / mo

In: $10.78Out: $14.52

OpenAI: GPT-5.3-Codex$271.25 / mo

In: $61.25Out: $210.00

Estimated Cost Delta

GLM-5.2 is estimated to save $245.95/month ($2,951/year).

Based on 50M tokens (30% gen)

Key Selection Recommendations

1
GLM-5.2:Pick GLM-5.2 when you are optimizing output cost.
2
GLM-5.2:Pick GLM-5.2 for million-token RAG or long-document jobs.

Recommended Workload Routing

Repo / coding agentsinsufficient data

Need SWE-bench on both sides.

High-volume chatGLM-5.2

Lower output list price ($0.97/1M).

Voice / low-latency UIinsufficient data

Need TTFT on both sides.

Long-document RAGGLM-5.2

Larger window (1M).

Screenshots / visionGLM-5.2

GLM-5.2 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	GLM-5.2	Lower output list price ($0.97/1M).
Voice / low-latency UI	insufficient data	Need TTFT on both sides.
Long-document RAG	GLM-5.2	Larger window (1M).
Screenshots / vision	GLM-5.2	GLM-5.2 is the side marked multimodal in the catalog.

Related Editorial Dispatches & Benchmark Notes

View all news

newsAug 16, 2026

GLM-5.2 vs GLM 5V Turbo Price and SWE-bench 2026

GLM-5.2 undercuts GLM 5V Turbo by 74.2% on input at $0.31/1M, with 1,492 Elo and 69.3% SWE-bench in dated 2026 snapshots.

launchJun 18, 2026

GLM-5.2 remains the prior Zhipu flagship for upgrade pairs

Strong Chinese/English coding. 5.3 is the new row; 5.2 stays so the delta is visible.

Community Sentiment

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LIVE

Zhipu

GLM-5.2

Elo 1,492

LiveBench65.2%

SWE-bench69.3%

Speed84 tok/s

Output cost$0.97/1M

OpenAI

OpenAI: GPT-5.3-Codex

Elo n/a

LiveBench—

SWE-bench—

Speed—

Output cost$14/1M

Frequently Asked Questions

Which is better overall, GLM-5.2 or OpenAI: GPT-5.3-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, GLM-5.2 or OpenAI: GPT-5.3-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?: GLM-5.2 output tokens are $0.97/1M versus $14/1M. Input prices and retry rates still move the real bill.
Which is faster, GLM-5.2 or OpenAI: GPT-5.3-Codex?: We do not have TTFT for both models.
Which has the larger context window?: GLM-5.2 accepts 1M tokens versus 400k.
Can I self-host either model?: GLM-5.2 is marked open-weights in our catalog. The other side is a closed API. Check the provider license before you ship weights.
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. GLM-5.2 and OpenAI: GPT-5.3-Codex Elo cells are dated snapshots from the named source — we do not compute Arena ourselves.

Similar Head-to-Head Comparisons

All GLM-5.2 matchups →|All OpenAI: GPT-5.3-Codex matchups →

GLM-5.2 vs GLM-5.3 (next glm)GPT-4.5 Orion vs GLM-5.2 GPT-5.6 Terra vs GLM-5.2 GPT-5 vs GLM-5.2 GPT-5.6 Sol vs GLM-5.2 OpenAI: o1 vs GLM-5.2

GLM-5.2 vs OpenAI: GPT-5.3-Codex benchmark

Interactive Comparison Diagram

Matchup Breakdown

Tug-of-War Matchup Matrix

Category wins across intelligence, speed, and pricing efficiency.

GLM-5.2 (10)vsOpenAI: GPT-5.3-Codex (0)

GLM-5.2: 10W (100%)Overall: GLM-5.2OpenAI: GPT-5.3-Codex: 0W (0%)

← GLM-5.2OpenAI: GPT-5.3-Codex →

GLM-5.2 (5/5)

Intelligence & Reasoning

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

Preference Elo

1,492vs—

Coding Elo

1,504vs—

SWE-bench

69.3%vs—

LiveBench

65.2%vs—

GPQA Diamond

79.5%vs—

GLM-5.2: 5WOpenAI: GPT-5.3-Codex: 0W

GLM-5.2 (2/2)

Speed & Latency

Generation throughput and time to first token responsiveness

Output speed

84 tok/svs—

Time to first token

270 msvs—

GLM-5.2: 2WOpenAI: GPT-5.3-Codex: 0W

GLM-5.2 (3/3)

Pricing & Capacity

Cost per million tokens and max context window length

Output price

$0.97/1Mvs$14/1M

Input price

$0.31/1Mvs$1.75/1M

Context window

1Mvs400k

GLM-5.2: 3WOpenAI: GPT-5.3-Codex: 0W

Recommended Workload Routing

Repo / coding agentsinsufficient data

Need SWE-bench on both sides.

High-volume chatGLM-5.2

Lower output list price ($0.97/1M).

Voice / low-latency UIinsufficient data

Need TTFT on both sides.

Long-document RAGGLM-5.2

Larger window (1M).

Screenshots / visionGLM-5.2

GLM-5.2 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	GLM-5.2	Lower output list price ($0.97/1M).
Voice / low-latency UI	insufficient data	Need TTFT on both sides.
Long-document RAG	GLM-5.2	Larger window (1M).
Screenshots / vision	GLM-5.2	GLM-5.2 is the side marked multimodal in the catalog.

Frequently Asked Questions

Which is better overall, GLM-5.2 or OpenAI: GPT-5.3-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, GLM-5.2 or OpenAI: GPT-5.3-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?

GLM-5.2 output tokens are $0.97/1M versus $14/1M. Input prices and retry rates still move the real bill.

Which is faster, GLM-5.2 or OpenAI: GPT-5.3-Codex?

We do not have TTFT for both models.

Which has the larger context window?

GLM-5.2 accepts 1M tokens versus 400k.

Can I self-host either model?

GLM-5.2 is marked open-weights in our catalog. The other side is a closed API. Check the provider license before you ship weights.

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. GLM-5.2 and OpenAI: GPT-5.3-Codex Elo cells are dated snapshots from the named source — we do not compute Arena ourselves.

Swap or Add Any Model to this Matchup

Interactive Comparison Diagram

Tug-of-War Matchup Matrix

Intelligence & Reasoning

Speed & Latency

Pricing & Capacity

Multi-Dimensional Capability Radar

No shared data

No shared data

GLM-5.2

Full Benchmark Score Matrix

Workload Cost & Savings Calculator

Key Selection Recommendations

Recommended Workload Routing

Related Editorial Dispatches & Benchmark Notes

GLM-5.2 vs GLM 5V Turbo Price and SWE-bench 2026

GLM-5.2 remains the prior Zhipu flagship for upgrade pairs

Cast Your Matchup Vote

Community Discussions (0)

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CompareLLM Matrix

GLM-5.2

OpenAI: GPT-5.3-Codex

Frequently Asked Questions

Related news

Similar Head-to-Head Comparisons

Swap or Add Any Model to this Matchup

Interactive Comparison Diagram

Tug-of-War Matchup Matrix

Intelligence & Reasoning

Speed & Latency

Pricing & Capacity

Multi-Dimensional Capability Radar

No shared data

No shared data

GLM-5.2

Full Benchmark Score Matrix

Workload Cost & Savings Calculator

Key Selection Recommendations

Recommended Workload Routing

Related Editorial Dispatches & Benchmark Notes

GLM-5.2 vs GLM 5V Turbo Price and SWE-bench 2026

GLM-5.2 remains the prior Zhipu flagship for upgrade pairs

Cast Your Matchup Vote

Community Discussions (0)

Share card

CompareLLM Matrix

GLM-5.2

OpenAI: GPT-5.3-Codex

Frequently Asked Questions

Related news

Similar Head-to-Head Comparisons