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

Claude 3 Opus vs Z.ai: GLM 5.2 (batch) benchmark

Name: Claude 3 Opus vs Z.ai: GLM 5.2 (batch) AI benchmark comparison
Creator: CompareLLM
License: https://creativecommons.org/licenses/by/4.0/

This page compares Claude 3 Opus (Anthropic) and Z.ai: GLM 5.2 (batch) (Zhipu) using the latest snapshots we have as of Aug 17, 2026. Z.ai: GLM 5.2 (batch) wins on output price at $2.2/1M. Z.ai: GLM 5.2 (batch) has the larger context window (512k 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

Zhipu

Z.ai: GLM 5.2 (batch)

Auto-discovered from OpenRouter (z-ai/glm-5.2:batch). Preview until a second source matches.

$2.2/1M 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)vsZ.ai: GLM 5.2 (batch) (3)

Claude 3 Opus: 6W (67%)Overall: Claude 3 OpusZ.ai: GLM 5.2 (batch): 3W (33%)

← Claude 3 OpusZ.ai: GLM 5.2 (batch) →

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: 4WZ.ai: GLM 5.2 (batch): 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: 2WZ.ai: GLM 5.2 (batch): 0W

Z.ai: GLM 5.2 (batch) (3/3)

Pricing & Capacity

Cost per million tokens and max context window length

Output price

$75/1Mvs$2.2/1M

Input price

$15/1Mvs$0.7/1M

Context window

200kvs512k

Claude 3 Opus: 0WZ.ai: GLM 5.2 (batch): 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

Token Price Efficiency

Z.ai: GLM 5.2 (batch)

$72.80/1M 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

$15.00 / 1M

In $Low is better

$0.70 / 1M+2043%

Out $

Low is better

$75.00 / 1M

Out $Low is better

$2.20 / 1M+3309%

Context

High is better

200k

ContextHigh is better

512k+156%

Interactive Simulator (USD)

Workload Cost & Savings Calculator

Simulate monthly production API costs in USD (US Dollar).

Save up to 97% with Z.ai: GLM 5.2 (batch)

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: $525Out: $1,125

Z.ai: GLM 5.2 (batch)$57.50 / mo

In: $24.5Out: $33

Estimated Cost Delta

Z.ai: GLM 5.2 (batch) is estimated to save $1,592.50/month ($19,110/year).

Based on 50M tokens (30% gen)

Key Selection Recommendations

1
Z.ai: GLM 5.2 (batch):Pick Z.ai: GLM 5.2 (batch) when you are optimizing output cost.

Recommended Workload Routing

Repo / coding agentsinsufficient data

Need SWE-bench on both sides.

High-volume chatZ.ai: GLM 5.2 (batch)

Lower output list price ($2.2/1M).

Voice / low-latency UIinsufficient data

Need TTFT on both sides.

Long-document RAGZ.ai: GLM 5.2 (batch)

Larger window (512k).

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	Z.ai: GLM 5.2 (batch)	Lower output list price ($2.2/1M).
Voice / low-latency UI	insufficient data	Need TTFT on both sides.
Long-document RAG	Z.ai: GLM 5.2 (batch)	Larger window (512k).
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

Zhipu

Z.ai: GLM 5.2 (batch)

Elo n/a

LiveBench—

SWE-bench—

Speed—

Output cost$2.2/1M

Frequently Asked Questions

Which is better overall, Claude 3 Opus or Z.ai: GLM 5.2 (batch)?: 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 Z.ai: GLM 5.2 (batch)?: 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?: Z.ai: GLM 5.2 (batch) output tokens are $2.2/1M versus $75/1M. Input prices and retry rates still move the real bill.
Which is faster, Claude 3 Opus or Z.ai: GLM 5.2 (batch)?: We do not have TTFT for both models.
Which has the larger context window?: Z.ai: GLM 5.2 (batch) accepts 512k 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 Z.ai: GLM 5.2 (batch) 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 Z.ai: GLM 5.2 (batch) 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 Claude Opus 5 vs Claude 3 Opus Claude Fable 5 vs Claude 3 Opus

Claude 3 Opus vs Z.ai: GLM 5.2 (batch) benchmark

Interactive Comparison Diagram

Matchup Breakdown

Tug-of-War Matchup Matrix

Category wins across intelligence, speed, and pricing efficiency.

Claude 3 Opus (6)vsZ.ai: GLM 5.2 (batch) (3)

Claude 3 Opus: 6W (67%)Overall: Claude 3 OpusZ.ai: GLM 5.2 (batch): 3W (33%)

← Claude 3 OpusZ.ai: GLM 5.2 (batch) →

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: 4WZ.ai: GLM 5.2 (batch): 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: 2WZ.ai: GLM 5.2 (batch): 0W

Z.ai: GLM 5.2 (batch) (3/3)

Pricing & Capacity

Cost per million tokens and max context window length

Output price

$75/1Mvs$2.2/1M

Input price

$15/1Mvs$0.7/1M

Context window

200kvs512k

Claude 3 Opus: 0WZ.ai: GLM 5.2 (batch): 3W

Recommended Workload Routing

Repo / coding agentsinsufficient data

Need SWE-bench on both sides.

High-volume chatZ.ai: GLM 5.2 (batch)

Lower output list price ($2.2/1M).

Voice / low-latency UIinsufficient data

Need TTFT on both sides.

Long-document RAGZ.ai: GLM 5.2 (batch)

Larger window (512k).

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	Z.ai: GLM 5.2 (batch)	Lower output list price ($2.2/1M).
Voice / low-latency UI	insufficient data	Need TTFT on both sides.
Long-document RAG	Z.ai: GLM 5.2 (batch)	Larger window (512k).
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 Z.ai: GLM 5.2 (batch)?

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 Z.ai: GLM 5.2 (batch)?

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?

Z.ai: GLM 5.2 (batch) output tokens are $2.2/1M versus $75/1M. Input prices and retry rates still move the real bill.

Which is faster, Claude 3 Opus or Z.ai: GLM 5.2 (batch)?

We do not have TTFT for both models.

Which has the larger context window?

Z.ai: GLM 5.2 (batch) accepts 512k 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 Z.ai: GLM 5.2 (batch) Elo cells are dated snapshots from the named source — we do not compute Arena ourselves.