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

Anthropic: Claude Sonnet 4.6 (batch) vs GLM-5.3 benchmark

Name: Anthropic: Claude Sonnet 4.6 (batch) vs GLM-5.3 AI benchmark comparison
Creator: CompareLLM
License: https://creativecommons.org/licenses/by/4.0/

This page compares Anthropic: Claude Sonnet 4.6 (batch) (Anthropic) and GLM-5.3 (Zhipu) using the latest snapshots we have as of Aug 17, 2026. GLM-5.3 wins on output price at $1.8/1M. Anthropic: Claude Sonnet 4.6 (batch) 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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Anthropic

Anthropic: Claude Sonnet 4.6 (batch)

Auto-discovered from OpenRouter (anthropic/claude-sonnet-4.6:batch). Preview until a second source matches.

$7.5/1M out

Zhipu

GLM-5.3

Z.ai Aug 14 2026 post-train of the GLM-5.2 744B base. Coding-plan live; open weights promised after a two-week safety review (z.ai/blog/glm-5.3).

Elo 1,558$1.8/1M 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.

Anthropic: Claude Sonnet 4.6 (batch) (1)vsGLM-5.3 (9)

Anthropic: Claude Sonnet 4.6 (batch): 1W (10%)Overall: GLM-5.3GLM-5.3: 9W (90%)

← Anthropic: Claude Sonnet 4.6 (batch)GLM-5.3 →

GLM-5.3 (5/5)

Intelligence & Reasoning

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

Preference Elo

—vs1,558

Coding Elo

—vs1,586

SWE-bench

—vs76.4%

LiveBench

—vs70.8%

GPQA Diamond

—vs83.2%

Anthropic: Claude Sonnet 4.6 (batch): 0WGLM-5.3: 5W

GLM-5.3 (2/2)

Speed & Latency

Generation throughput and time to first token responsiveness

Output speed

—vs90 tok/s

Time to first token

—vs255 ms

Anthropic: Claude Sonnet 4.6 (batch): 0WGLM-5.3: 2W

GLM-5.3 (2/3)

Pricing & Capacity

Cost per million tokens and max context window length

Output price

$7.5/1Mvs$1.8/1M

Input price

$1.5/1Mvs$0.5/1M

Context window

1Mvs200k

Anthropic: Claude Sonnet 4.6 (batch): 1WGLM-5.3: 2W

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-5.3 5/6

Preference Elo

No shared data

Throughput Speed

No shared data

Price Efficiency

GLM-5.3

$5.70/1M cheaper

Full Benchmark Score Matrix

—

Elo

High is better

—

EloHigh is better

1,558

Code Elo

High is better

—

Code EloHigh is better

1,586

LiveBench

High is better

—

LiveBenchHigh is better

70.8%

SWE-bench

High is better

—

SWE-benchHigh is better

76.4%

GPQA

High is better

—

GPQAHigh is better

83.2%

TTFT

Low is better

—

TTFTLow is better

255 ms

Speed

High is better

—

SpeedHigh is better

90 tok/s

In $

Low is better

$1.5/1M

In $Low is better

$0.5/1M+200%

Out $

Low is better

$7.5/1M

Out $Low is better

$1.8/1M+317%

Context

High is better

+400%1M

ContextHigh is better

200k

Interactive Simulator

Workload Cost & Savings Calculator

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

Save up to 73% with GLM-5.3

Monthly Volume50M tokens/mo

Quick Presets:

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

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

Anthropic: Claude Sonnet 4.6 (batch)$165.00 / mo

In: $52.50Out: $112.50

GLM-5.3$44.50 / mo

In: $17.50Out: $27.00

Estimated Cost Delta

GLM-5.3 is estimated to save $120.50/month ($1,446/year).

Based on 50M tokens (30% gen)

Key Selection Recommendations

1
GLM-5.3:Pick GLM-5.3 when you are optimizing output cost.
2
Anthropic: Claude Sonnet 4.6 (batch):Pick Anthropic: Claude Sonnet 4.6 (batch) for million-token RAG or long-document jobs.

Recommended Workload Routing

Repo / coding agentsinsufficient data

Need SWE-bench on both sides.

High-volume chatGLM-5.3

Lower output list price ($1.8/1M).

Voice / low-latency UIinsufficient data

Need TTFT on both sides.

Long-document RAGAnthropic: Claude Sonnet 4.6 (batch)

Larger window (1M).

Screenshots / visionGLM-5.3

GLM-5.3 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-5.3	Lower output list price ($1.8/1M).
Voice / low-latency UI	insufficient data	Need TTFT on both sides.
Long-document RAG	Anthropic: Claude Sonnet 4.6 (batch)	Larger window (1M).
Screenshots / vision	GLM-5.3	GLM-5.3 is the side marked multimodal in the catalog.

Related Editorial Dispatches & Benchmark Notes

View all news

launchAug 14, 2026

GLM-5.3 (Aug 14): Z.ai post-train of the 5.2 744B base

Coding-plan live; open weights promised after a two-week safety review. Newest Zhipu row.

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

Anthropic

Anthropic: Claude Sonnet 4.6 (batch)

Elo n/a

LiveBench—

SWE-bench—

Speed—

Output cost$7.5/1M

Zhipu

GLM-5.3

Elo 1,558

LiveBench70.8%

SWE-bench76.4%

Speed90 tok/s

Output cost$1.8/1M

Frequently Asked Questions

Which is better overall, Anthropic: Claude Sonnet 4.6 (batch) or GLM-5.3?: 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, Anthropic: Claude Sonnet 4.6 (batch) or GLM-5.3?: 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-5.3 output tokens are $1.8/1M versus $7.5/1M. Input prices and retry rates still move the real bill.
Which is faster, Anthropic: Claude Sonnet 4.6 (batch) or GLM-5.3?: We do not have TTFT for both models.
Which has the larger context window?: Anthropic: Claude Sonnet 4.6 (batch) accepts 1M 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. Anthropic: Claude Sonnet 4.6 (batch) and GLM-5.3 Elo cells are dated snapshots from the named source — we do not compute Arena ourselves.

Similar Head-to-Head Comparisons

All Anthropic: Claude Sonnet 4.6 (batch) matchups →|All GLM-5.3 matchups →

GLM-5.3 vs Z.ai: GLM 5V Turbo (previous glm)Claude Opus 4.5 vs GLM-5.3 Claude Opus 4.6 vs GLM-5.3 Claude Sonnet 4.5 vs GLM-5.3 Claude Opus 5 vs GLM-5.3 Claude Fable 5 vs GLM-5.3

Anthropic: Claude Sonnet 4.6 (batch) vs GLM-5.3 benchmark

Interactive Comparison Diagram

Matchup Breakdown

Tug-of-War Matchup Matrix

Category wins across intelligence, speed, and pricing efficiency.

Anthropic: Claude Sonnet 4.6 (batch) (1)vsGLM-5.3 (9)

Anthropic: Claude Sonnet 4.6 (batch): 1W (10%)Overall: GLM-5.3GLM-5.3: 9W (90%)

← Anthropic: Claude Sonnet 4.6 (batch)GLM-5.3 →

GLM-5.3 (5/5)

Intelligence & Reasoning

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

Preference Elo

—vs1,558

Coding Elo

—vs1,586

SWE-bench

—vs76.4%

LiveBench

—vs70.8%

GPQA Diamond

—vs83.2%

Anthropic: Claude Sonnet 4.6 (batch): 0WGLM-5.3: 5W

GLM-5.3 (2/2)

Speed & Latency

Generation throughput and time to first token responsiveness

Output speed

—vs90 tok/s

Time to first token

—vs255 ms

Anthropic: Claude Sonnet 4.6 (batch): 0WGLM-5.3: 2W

GLM-5.3 (2/3)

Pricing & Capacity

Cost per million tokens and max context window length

Output price

$7.5/1Mvs$1.8/1M

Input price

$1.5/1Mvs$0.5/1M

Context window

1Mvs200k

Anthropic: Claude Sonnet 4.6 (batch): 1WGLM-5.3: 2W

Recommended Workload Routing

Repo / coding agentsinsufficient data

Need SWE-bench on both sides.

High-volume chatGLM-5.3

Lower output list price ($1.8/1M).

Voice / low-latency UIinsufficient data

Need TTFT on both sides.

Long-document RAGAnthropic: Claude Sonnet 4.6 (batch)

Larger window (1M).

Screenshots / visionGLM-5.3

GLM-5.3 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-5.3	Lower output list price ($1.8/1M).
Voice / low-latency UI	insufficient data	Need TTFT on both sides.
Long-document RAG	Anthropic: Claude Sonnet 4.6 (batch)	Larger window (1M).
Screenshots / vision	GLM-5.3	GLM-5.3 is the side marked multimodal in the catalog.

Frequently Asked Questions

Which is better overall, Anthropic: Claude Sonnet 4.6 (batch) or GLM-5.3?

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, Anthropic: Claude Sonnet 4.6 (batch) or GLM-5.3?

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-5.3 output tokens are $1.8/1M versus $7.5/1M. Input prices and retry rates still move the real bill.

Which is faster, Anthropic: Claude Sonnet 4.6 (batch) or GLM-5.3?

We do not have TTFT for both models.

Which has the larger context window?

Anthropic: Claude Sonnet 4.6 (batch) accepts 1M 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. Anthropic: Claude Sonnet 4.6 (batch) and GLM-5.3 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-5.3

Full Benchmark Score Matrix

Workload Cost & Savings Calculator

Key Selection Recommendations

Recommended Workload Routing

Related Editorial Dispatches & Benchmark Notes

GLM-5.3 (Aug 14): Z.ai post-train of the 5.2 744B base

GLM-5.2 remains the prior Zhipu flagship for upgrade pairs

Cast Your Matchup Vote

Community Discussions (0)

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CompareLLM Matrix

Anthropic: Claude Sonnet 4.6 (batch)

GLM-5.3

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-5.3

Full Benchmark Score Matrix

Workload Cost & Savings Calculator

Key Selection Recommendations

Recommended Workload Routing

Related Editorial Dispatches & Benchmark Notes

GLM-5.3 (Aug 14): Z.ai post-train of the 5.2 744B base

GLM-5.2 remains the prior Zhipu flagship for upgrade pairs

Cast Your Matchup Vote

Community Discussions (0)

Share card

CompareLLM Matrix

Anthropic: Claude Sonnet 4.6 (batch)

GLM-5.3

Frequently Asked Questions

Related news

Similar Head-to-Head Comparisons