Pairwise benchmark snapshot · Aug 16, 2026

Claude 3.7 Sonnet vs GLM-5.2 benchmark

Name: Claude 3.7 Sonnet vs GLM-5.2 AI benchmark comparison
Creator: CompareLLM
License: https://creativecommons.org/licenses/by/4.0/

This page compares Claude 3.7 Sonnet (Anthropic) and GLM-5.2 (Zhipu) using the latest snapshots we have as of Aug 16, 2026. On preference Elo, GLM-5.2 is ahead by 130 points (1,492 vs 1,362; seed-bootstrap (Aug 1, 2026)). On SWE-bench coding, Claude 3.7 Sonnet resolves 70.3% versus 69.3% (seed-bootstrap (Aug 1, 2026)). Claude 3.7 Sonnet streams faster (85 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 3.7 Sonnet

Hybrid-reasoning Sonnet from 2025. Kept for historical compare pages.

Elo 1,362$15/1M 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 Opus 4.6 vs Claude Sonnet 4.5 vs GPT-5

Interactive Comparison Diagram

Matchup Breakdown

Tug-of-War Matchup Matrix

Category wins across intelligence, speed, and pricing efficiency.

Claude 3.7 Sonnet (3)vsGLM-5.2 (7)

Claude 3.7 Sonnet: 3W (30%)Overall: GLM-5.2GLM-5.2: 7W (70%)

← Claude 3.7 SonnetGLM-5.2 →

GLM-5.2 (4/5)

Intelligence & Reasoning

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

Preference Elo

1,362vs1,492

Coding Elo

—vs1,504

SWE-bench

70.3%vs69.3%

LiveBench

58.4%vs65.2%

GPQA Diamond

78.5%vs79.5%

Claude 3.7 Sonnet: 1WGLM-5.2: 4W

Claude 3.7 Sonnet (2/2)

Speed & Latency

Generation throughput and time to first token responsiveness

Output speed

85 tok/svs84 tok/s

Time to first token

240 msvs270 ms

Claude 3.7 Sonnet: 2WGLM-5.2: 0W

GLM-5.2 (3/3)

Pricing & Capacity

Cost per million tokens and max context window length

Output price

$15/1Mvs$0.97/1M

Input price

$3/1Mvs$0.31/1M

Context window

200kvs1M

Claude 3.7 Sonnet: 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 AdvantageGLM-5.2 4/6

Preference Elo

GLM-5.2

130 pts advantage

Throughput Speed

Claude 3.7 Sonnet

1 tok/s faster

Price Efficiency

GLM-5.2

$14.03/1M cheaper

Full Benchmark Score Matrix

—

Elo

High is better

1,362

EloHigh is better

1,492+10%

Code Elo

High is better

—

Code EloHigh is better

1,504

LiveBench

High is better

58.4%

LiveBenchHigh is better

65.2%+12%

SWE-bench

High is better

+1%70.3%

SWE-benchHigh is better

69.3%

GPQA

High is better

78.5%

GPQAHigh is better

79.5%+1%

TTFT

Low is better

+13%240 ms

TTFTLow is better

270 ms

Speed

High is better

+1%85 tok/s

SpeedHigh is better

84 tok/s

In $

Low is better

$3/1M

In $Low is better

$0.31/1M+874%

Out $

Low is better

$15/1M

Out $Low is better

$0.97/1M+1450%

Context

High is better

200k

ContextHigh is better

1M+424%

Interactive Simulator

Workload Cost & Savings Calculator

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

Save up to 92% 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 3.7 Sonnet$330.00 / mo

In: $105.00Out: $225.00

GLM-5.2$25.30 / mo

In: $10.78Out: $14.52

Estimated Cost Delta

GLM-5.2 is estimated to save $304.70/month ($3,656/year).

Based on 50M tokens (30% gen)

Key Selection Recommendations

1
Claude 3.7 Sonnet:Pick Claude 3.7 Sonnet when repo-level coding accuracy is the constraint.
2
GLM-5.2:Pick GLM-5.2 when you are optimizing output cost.
3
Claude 3.7 Sonnet:Pick Claude 3.7 Sonnet when time-to-first-token matters more than peak Elo.

Recommended Workload Routing

Repo / coding agentsClaude 3.7 Sonnet

Higher SWE-bench (70.3%).

High-volume chatGLM-5.2

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

Voice / low-latency UIClaude 3.7 Sonnet

Lower TTFT (240 ms).

Long-document RAGGLM-5.2

Larger window (1M).

Screenshots / visionGLM-5.2

Both accept images. Defaulting to the higher-Elo side (GLM-5.2).

Target Workload	Recommended Pick	Evaluation Rationale
Repo / coding agents	Claude 3.7 Sonnet	Higher SWE-bench (70.3%).
High-volume chat	GLM-5.2	Lower output list price ($0.97/1M).
Voice / low-latency UI	Claude 3.7 Sonnet	Lower TTFT (240 ms).
Long-document RAG	GLM-5.2	Larger window (1M).
Screenshots / vision	GLM-5.2	Both accept images. Defaulting to the higher-Elo side (GLM-5.2).

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.

newsFeb 25, 2025

Claude 3.7 Sonnet stays as a historical hybrid-reasoning baseline

2025 hybrid-reasoning Sonnet. Deprecated for buying, kept for old compare URLs and “what did 3.7 score?”

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LIVE

Anthropic

Claude 3.7 Sonnet

Elo 1,362

LiveBench58.4%

SWE-bench70.3%

Speed85 tok/s

Output cost$15/1M

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 3.7 Sonnet or GLM-5.2?: GLM-5.2 has the higher preference Elo in our latest snapshot (1,492). “Better” still depends on coding, price, and latency — see the table.
Which is better at coding, Claude 3.7 Sonnet or GLM-5.2?: Claude 3.7 Sonnet leads SWE-bench at 70.3% 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 $15/1M. Input prices and retry rates still move the real bill.
Which is faster, Claude 3.7 Sonnet or GLM-5.2?: Claude 3.7 Sonnet has the lower time-to-first-token (240 ms vs 270 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 200k.
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 3.7 Sonnet 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 3.7 Sonnet matchups →|All GLM-5.2 matchups →

Claude 3.7 Sonnet vs Claude 3.5 Sonnet (previous sonnet)Claude 3.7 Sonnet vs Claude Sonnet 4 (next sonnet)GLM-5.2 vs GLM-5.3 (next glm)Claude Opus 4.5 vs GLM-5.2 Claude Opus 4.6 vs GLM-5.2 Claude Sonnet 4.5 vs GLM-5.2

Claude 3.7 Sonnet vs GLM-5.2 benchmark

Interactive Comparison Diagram

Matchup Breakdown

Tug-of-War Matchup Matrix

Category wins across intelligence, speed, and pricing efficiency.

Claude 3.7 Sonnet (3)vsGLM-5.2 (7)

Claude 3.7 Sonnet: 3W (30%)Overall: GLM-5.2GLM-5.2: 7W (70%)

← Claude 3.7 SonnetGLM-5.2 →

GLM-5.2 (4/5)

Intelligence & Reasoning

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

Preference Elo

1,362vs1,492

Coding Elo

—vs1,504

SWE-bench

70.3%vs69.3%

LiveBench

58.4%vs65.2%

GPQA Diamond

78.5%vs79.5%

Claude 3.7 Sonnet: 1WGLM-5.2: 4W

Claude 3.7 Sonnet (2/2)

Speed & Latency

Generation throughput and time to first token responsiveness

Output speed

85 tok/svs84 tok/s

Time to first token

240 msvs270 ms

Claude 3.7 Sonnet: 2WGLM-5.2: 0W

GLM-5.2 (3/3)

Pricing & Capacity

Cost per million tokens and max context window length

Output price

$15/1Mvs$0.97/1M

Input price

$3/1Mvs$0.31/1M

Context window

200kvs1M

Claude 3.7 Sonnet: 0WGLM-5.2: 3W

Recommended Workload Routing

Repo / coding agentsClaude 3.7 Sonnet

Higher SWE-bench (70.3%).

High-volume chatGLM-5.2

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

Voice / low-latency UIClaude 3.7 Sonnet

Lower TTFT (240 ms).

Long-document RAGGLM-5.2

Larger window (1M).

Screenshots / visionGLM-5.2

Both accept images. Defaulting to the higher-Elo side (GLM-5.2).

Target Workload	Recommended Pick	Evaluation Rationale
Repo / coding agents	Claude 3.7 Sonnet	Higher SWE-bench (70.3%).
High-volume chat	GLM-5.2	Lower output list price ($0.97/1M).
Voice / low-latency UI	Claude 3.7 Sonnet	Lower TTFT (240 ms).
Long-document RAG	GLM-5.2	Larger window (1M).
Screenshots / vision	GLM-5.2	Both accept images. Defaulting to the higher-Elo side (GLM-5.2).

Frequently Asked Questions

Which is better overall, Claude 3.7 Sonnet or GLM-5.2?

GLM-5.2 has the higher preference Elo in our latest snapshot (1,492). “Better” still depends on coding, price, and latency — see the table.

Which is better at coding, Claude 3.7 Sonnet or GLM-5.2?

Claude 3.7 Sonnet leads SWE-bench at 70.3% 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 $15/1M. Input prices and retry rates still move the real bill.

Which is faster, Claude 3.7 Sonnet or GLM-5.2?

Claude 3.7 Sonnet has the lower time-to-first-token (240 ms vs 270 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 200k.

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 3.7 Sonnet 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

GLM-5.2

Claude 3.7 Sonnet

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 3.7 Sonnet stays as a historical hybrid-reasoning baseline

Cast Your Matchup Vote

Community Discussions (0)

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CompareLLM Matrix

Claude 3.7 Sonnet

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

GLM-5.2

Claude 3.7 Sonnet

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 3.7 Sonnet stays as a historical hybrid-reasoning baseline

Cast Your Matchup Vote

Community Discussions (0)

Share card

CompareLLM Matrix

Claude 3.7 Sonnet

GLM-5.2

Frequently Asked Questions

Related news

Similar Head-to-Head Comparisons