Pairwise benchmark snapshot · Aug 16, 2026

Claude Opus 4.6 vs GLM-5.2 benchmark

Name: Claude Opus 4.6 vs GLM-5.2 AI benchmark comparison
Creator: CompareLLM
License: https://creativecommons.org/licenses/by/4.0/

This page compares Claude Opus 4.6 (Anthropic) and GLM-5.2 (Zhipu) using the latest snapshots we have as of Aug 16, 2026. On preference Elo, Claude Opus 4.6 is ahead by 82 points (1,574 vs 1,492; seed-bootstrap (Aug 1, 2026)). On SWE-bench coding, Claude Opus 4.6 resolves 75.9% versus 69.3% (seed-bootstrap (Aug 1, 2026)). GLM-5.2 streams faster (84 tok/s) while GLM-5.2 is the cheaper output token ($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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Anthropic

Claude Opus 4.6

Follow-on Opus release. Slightly behind 4.5 on official SWE-bench bash-only in the last published sweep; stronger long-horizon agent traces.

Elo 1,574$25/1M out

Zhipu

GLM-5.2

Zhipu flagship. Strong Chinese/English coding and agents.

Elo 1,492$0.9680000000000001/1M out

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Quick vs:vs Claude Opus 4.5 vs Claude Sonnet 4.5 vs Claude 3.7 Sonnet vs GPT-5

Interactive Comparison Diagram

Matchup Breakdown

Tug-of-War Matchup Matrix

Category wins across intelligence, speed, and pricing efficiency.

Claude Opus 4.6 (5)vsGLM-5.2 (5)

Claude Opus 4.6: 5W (50%)Overall: Even matchupGLM-5.2: 5W (50%)

← Claude Opus 4.6GLM-5.2 →

Claude Opus 4.6 (5/5)

Intelligence & Reasoning

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

Preference Elo

1,574vs1,492

Coding Elo

1,570vs1,504

SWE-bench

75.9%vs69.3%

LiveBench

72%vs65.2%

GPQA Diamond

84.8%vs79.5%

Claude Opus 4.6: 5WGLM-5.2: 0W

GLM-5.2 (2/2)

Speed & Latency

Generation throughput and time to first token responsiveness

Output speed

64 tok/svs84 tok/s

Time to first token

360 msvs270 ms

Claude Opus 4.6: 0WGLM-5.2: 2W

GLM-5.2 (3/3)

Pricing & Capacity

Cost per million tokens and max context window length

Output price

$25/1Mvs$0.97/1M

Input price

$5/1Mvs$0.31/1M

Context window

1Mvs1M

Claude Opus 4.6: 0WGLM-5.2: 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 AdvantageEven 3–3

Preference Elo

Claude Opus 4.6

82 pts advantage

Throughput Speed

GLM-5.2

20 tok/s faster

Price Efficiency

GLM-5.2

$24.03/1M cheaper

Full Benchmark Score Matrix

—

Elo

High is better

+5%1,574

EloHigh is better

1,492

Code Elo

High is better

+4%1,570

Code EloHigh is better

1,504

LiveBench

High is better

+10%72%

LiveBenchHigh is better

65.2%

SWE-bench

High is better

+10%75.9%

SWE-benchHigh is better

69.3%

GPQA

High is better

+7%84.8%

GPQAHigh is better

79.5%

TTFT

Low is better

360 ms

TTFTLow is better

270 ms+33%

Speed

High is better

64 tok/s

SpeedHigh is better

84 tok/s+31%

In $

Low is better

$5/1M

In $Low is better

$0.31/1M+1523%

Out $

Low is better

$25/1M

Out $Low is better

$0.97/1M+2483%

Context

High is better

ContextHigh is better

1M+5%

Interactive Simulator

Workload Cost & Savings Calculator

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

Save up to 95% 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)

Claude Opus 4.6$550.00 / mo

In: $175.00Out: $375.00

GLM-5.2$25.30 / mo

In: $10.78Out: $14.52

Estimated Cost Delta

GLM-5.2 is estimated to save $524.70/month ($6,296/year).

Based on 50M tokens (30% gen)

Key Selection Recommendations

1
Claude Opus 4.6:Pick Claude Opus 4.6 when repo-level coding accuracy is the constraint.
2
GLM-5.2:Pick GLM-5.2 when you are optimizing output cost.
3
GLM-5.2:Pick GLM-5.2 when time-to-first-token matters more than peak Elo.

Recommended Workload Routing

Repo / coding agentsClaude Opus 4.6

Higher SWE-bench (75.9%).

High-volume chatGLM-5.2

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

Voice / low-latency UIGLM-5.2

Lower TTFT (270 ms).

Long-document RAGGLM-5.2

Larger window (1M).

Screenshots / visionClaude Opus 4.6

Both accept images. Defaulting to the higher-Elo side (Claude Opus 4.6).

Target Workload	Recommended Pick	Evaluation Rationale
Repo / coding agents	Claude Opus 4.6	Higher SWE-bench (75.9%).
High-volume chat	GLM-5.2	Lower output list price ($0.97/1M).
Voice / low-latency UI	GLM-5.2	Lower TTFT (270 ms).
Long-document RAG	GLM-5.2	Larger window (1M).
Screenshots / vision	Claude Opus 4.6	Both accept images. Defaulting to the higher-Elo side (Claude Opus 4.6).

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.

launchMay 10, 2026

Claude Opus 4.6: the May follow-on that still shows up in old bookmarks

Slightly behind 4.5 on one official SWE-bench sweep; stronger long-horizon traces. We keep the row for old vs URLs.

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LIVE

Anthropic

Claude Opus 4.6

Elo 1,574

LiveBench72%

SWE-bench75.9%

Speed64 tok/s

Output cost$25/1M

Zhipu

GLM-5.2

Elo 1,492

LiveBench65.2%

SWE-bench69.3%

Speed84 tok/s

Output cost$0.97/1M

Frequently Asked Questions

Which is better overall, Claude Opus 4.6 or GLM-5.2?: Claude Opus 4.6 has the higher preference Elo in our latest snapshot (1,574). “Better” still depends on coding, price, and latency — see the table.
Which is better at coding, Claude Opus 4.6 or GLM-5.2?: Claude Opus 4.6 leads SWE-bench at 75.9% vs 69.3%. SWE-bench is one harness, not your repo.
Which is cheaper to run in production?: GLM-5.2 output tokens are $0.97/1M versus $25/1M. Input prices and retry rates still move the real bill.
Which is faster, Claude Opus 4.6 or GLM-5.2?: GLM-5.2 has the lower time-to-first-token (270 ms vs 360 ms). Tokens/sec is a separate column if you care about long completions.
Which has the larger context window?: GLM-5.2 accepts 1M tokens versus 1M.
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. Claude Opus 4.6 and GLM-5.2 Elo cells are dated snapshots from the named source — we do not compute Arena ourselves.

Similar Head-to-Head Comparisons

All Claude Opus 4.6 matchups →|All GLM-5.2 matchups →

Claude Opus 4.6 vs Claude Opus 4.5 (previous opus)Claude Opus 4.6 vs Claude Opus 4.8 (next opus)GLM-5.2 vs GLM-5.3 (next glm)GLM-5.3 vs Claude Opus 4.6 Claude Sonnet 5 vs Claude Opus 4.6 Claude Fable 5 vs Claude Opus 4.6

Claude Opus 4.6 vs GLM-5.2 benchmark

Interactive Comparison Diagram

Matchup Breakdown

Tug-of-War Matchup Matrix

Category wins across intelligence, speed, and pricing efficiency.

Claude Opus 4.6 (5)vsGLM-5.2 (5)

Claude Opus 4.6: 5W (50%)Overall: Even matchupGLM-5.2: 5W (50%)

← Claude Opus 4.6GLM-5.2 →

Claude Opus 4.6 (5/5)

Intelligence & Reasoning

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

Preference Elo

1,574vs1,492

Coding Elo

1,570vs1,504

SWE-bench

75.9%vs69.3%

LiveBench

72%vs65.2%

GPQA Diamond

84.8%vs79.5%

Claude Opus 4.6: 5WGLM-5.2: 0W

GLM-5.2 (2/2)

Speed & Latency

Generation throughput and time to first token responsiveness

Output speed

64 tok/svs84 tok/s

Time to first token

360 msvs270 ms

Claude Opus 4.6: 0WGLM-5.2: 2W

GLM-5.2 (3/3)

Pricing & Capacity

Cost per million tokens and max context window length

Output price

$25/1Mvs$0.97/1M

Input price

$5/1Mvs$0.31/1M

Context window

1Mvs1M

Claude Opus 4.6: 0WGLM-5.2: 3W

Recommended Workload Routing

Repo / coding agentsClaude Opus 4.6

Higher SWE-bench (75.9%).

High-volume chatGLM-5.2

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

Voice / low-latency UIGLM-5.2

Lower TTFT (270 ms).

Long-document RAGGLM-5.2

Larger window (1M).

Screenshots / visionClaude Opus 4.6

Both accept images. Defaulting to the higher-Elo side (Claude Opus 4.6).

Target Workload	Recommended Pick	Evaluation Rationale
Repo / coding agents	Claude Opus 4.6	Higher SWE-bench (75.9%).
High-volume chat	GLM-5.2	Lower output list price ($0.97/1M).
Voice / low-latency UI	GLM-5.2	Lower TTFT (270 ms).
Long-document RAG	GLM-5.2	Larger window (1M).
Screenshots / vision	Claude Opus 4.6	Both accept images. Defaulting to the higher-Elo side (Claude Opus 4.6).

Frequently Asked Questions

Which is better overall, Claude Opus 4.6 or GLM-5.2?

Claude Opus 4.6 has the higher preference Elo in our latest snapshot (1,574). “Better” still depends on coding, price, and latency — see the table.

Which is better at coding, Claude Opus 4.6 or GLM-5.2?

Claude Opus 4.6 leads SWE-bench at 75.9% vs 69.3%. SWE-bench is one harness, not your repo.

Which is cheaper to run in production?

GLM-5.2 output tokens are $0.97/1M versus $25/1M. Input prices and retry rates still move the real bill.

Which is faster, Claude Opus 4.6 or GLM-5.2?

GLM-5.2 has the lower time-to-first-token (270 ms vs 360 ms). Tokens/sec is a separate column if you care about long completions.

Which has the larger context window?

GLM-5.2 accepts 1M tokens versus 1M.

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. Claude Opus 4.6 and GLM-5.2 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

Claude Opus 4.6

GLM-5.2

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

Claude Opus 4.6: the May follow-on that still shows up in old bookmarks

Cast Your Matchup Vote

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CompareLLM Matrix

Claude Opus 4.6

GLM-5.2

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

Claude Opus 4.6

GLM-5.2

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

Claude Opus 4.6: the May follow-on that still shows up in old bookmarks

Cast Your Matchup Vote

Community Discussions (0)

Share card

CompareLLM Matrix

Claude Opus 4.6

GLM-5.2

Frequently Asked Questions

Related news

Similar Head-to-Head Comparisons