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Model comparison

Claude Opus 4.5 vs GLM-5.2

Data verified

Head-to-head evidence from 23 shared benchmark results across 7 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.

64.22/100
Margin
0.3pts
← winning
63.96/100
1 category wins3 category wins

Public leaderboard positions: Claude Opus 4.5 #34 (Supported); GLM-5.2 #37 (Estimated). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.

Evidence parity. Claude Opus 4.5 and GLM-5.2 share 23 comparable benchmark results. 4 of 8 categories are comparable. 36 results are unique to Claude Opus 4.5; 20 to GLM-5.2.

Updated July 23, 2026
Shared results
23
Claude Opus 4.5 only
36
GLM-5.2 only
20
Comparable categories
4 / 8

Pick Claude Opus 4.5 if you want the stronger benchmark profile. GLM-5.2 only becomes the better choice if mathematics is the priority or you want the cheaper token bill.

Confidence note. This is a partial-evidence comparison with 23 shared benchmark results across 7 evidence categories; 4 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.

Why this result

Claude Opus 4.5 has the cleaner BenchAlign overall profile here, landing at 64.22 versus 63.96. It is a real lead, but still close enough that category-level strengths matter more than the headline number.

Claude Opus 4.5's sharpest advantage is in coding, where it averages 71.7 against 62.1. The single biggest benchmark swing on the page is HLE, 30.8% to 54.7%. GLM-5.2 does hit back in mathematics, so the answer changes if that is the part of the workload you care about most.

Claude Opus 4.5 is also the more expensive model on tokens at $5.00 input / $25.00 output per 1M tokens, versus $1.40 input / $4.40 output per 1M tokens for GLM-5.2. That is roughly 5.7x on output cost alone. GLM-5.2 is the reasoning model in the pair, while Claude Opus 4.5 is not. That usually helps on harder chain-of-thought-heavy tests, but it can also mean more latency and more token spend in real use. GLM-5.2 gives you the larger context window at 1M, compared with 200K for Claude Opus 4.5.

Category breakdown

Exact category averages are shown below. Not measured means BenchLM does not have enough sourced public coverage for that model and category.

Category scores and score margins for Claude Opus 4.5 and GLM-5.2
CategoryClaude Opus 4.5ΔGLM-5.2
MathClaude Opus 4.557.5Margin→ 38.4GLM-5.295.9
AgenticClaude Opus 4.562.6Margin→ 18.4GLM-5.281.0
CodingClaude Opus 4.571.7Margin← 9.6GLM-5.262.1
KnowledgeClaude Opus 4.558.1Margin→ 1.5GLM-5.259.6
ReasoningClaude Opus 4.564.4MarginNo overlapGLM-5.2Not measured
MultilingualClaude Opus 4.585.7MarginNo overlapGLM-5.2Not measured
MultimodalClaude Opus 4.569.9MarginNo overlapGLM-5.2Not measured
Inst. FollowingClaude Opus 4.569.5MarginNo overlapGLM-5.2Not measured

Decisive benchmark drivers

The largest measured benchmark gaps in this matchup, with exact reported values.

More
A · Claude Opus 4.5B · GLM-5.2

  1. HLE

    Knowledge
    Source ↗
    A 30.8%B 54.7%
    Winner: GLM-5.2Δ 23.9
    HLE: Claude Opus 4.5 scored 30.8%; GLM-5.2 scored 54.7%. GLM-5.2 wins this benchmark.

  2. Terminal-Bench 2.0

    Agentic
    Source ↗
    A 59.3%B 81%
    Winner: GLM-5.2Δ 21.7
    Terminal-Bench 2.0: Claude Opus 4.5 scored 59.3%; GLM-5.2 scored 81%. GLM-5.2 wins this benchmark.

  3. HMMT Feb 2026

    Math
    Source ↗
    A 85.3%B 92.5%
    Winner: GLM-5.2Δ 7.2
    HMMT Feb 2026: Claude Opus 4.5 scored 85.3%; GLM-5.2 scored 92.5%. GLM-5.2 wins this benchmark.

  4. SWE-bench Pro

    Coding
    Source ↗
    A 57.1%B 62.1%
    Winner: GLM-5.2Δ 5
    SWE-bench Pro: Claude Opus 4.5 scored 57.1%; GLM-5.2 scored 62.1%. GLM-5.2 wins this benchmark.

  5. GPQA

    Knowledge
    Source ↗
    A 87%B 91.2%
    Winner: GLM-5.2Δ 4.2
    GPQA: Claude Opus 4.5 scored 87%; GLM-5.2 scored 91.2%. GLM-5.2 wins this benchmark.

Operational comparison

Runtime and commercial metrics are compared only when both models have a complete sourced value.

MetricClaude Opus 4.5GLM-5.2Comparison
Input / output priceUSD per 1M tokensClaude Opus 4.5$5 input / $25 outputGLM-5.2$1.4 input / $4.4 outputGLM-5.2 has the lower combined listed price.
Generation speedtokens per secondClaude Opus 4.546 tok/sGLM-5.2Not availableA complete speed comparison is not available.
First-answer latencyseconds to first tokenClaude Opus 4.51.01 sGLM-5.2Not availableA complete latency comparison is not available.
Context windowmaximum listed tokensClaude Opus 4.5200KGLM-5.21MGLM-5.2 lists the larger context window.

Benchmark Deep Dive

AgenticGLM-5.2 wins
BenchmarkClaude Opus 4.5GLM-5.2Result
Terminal-Bench 2.0Source 59.3%81%GLM-5.2 leads
OSWorld-VerifiedSource 66.3%—Not comparable
OSWorldSource 66.3%—Not comparable
Claw-EvalSource 59.6%—Not comparable
QwenClawBenchSource 52.3%—Not comparable
τ³-bench resultsSource 70.2%—Not comparable
VITA-BenchSource 23.3%—Not comparable
DeepPlanningSource 26.4%—Not comparable
ToolathlonSource 43.5%48.2%GLM-5.2 leads
MCP AtlasSource 42.3%76.8%GLM-5.2 leads
MCP-TasksSource 71.8%—Not comparable
WideResearchSource 76.4%—Not comparable
CyberGymSource 50.6%—Not comparable
τ²-bench resultsSource 86.3%99.1%GLM-5.2 leads
Gert LabsSource 64.23%—Not comparable
JobBenchSource 32.3%—Not comparable
AA Agentic IndexSource —43.1%Not comparable
GDPval-AASource —50.7%Not comparable
GDPval-AASource —1514Not comparable
APEX-Agents-AASource —33.7%Not comparable
ResearchClawBenchSource —20.7%Not comparable
AA BriefcaseSource —1260Not comparable
AA AutomationBenchSource —27.8%Not comparable
AA EnterpriseOps-GymSource —42.7%Not comparable
AA Harvey LABSource —91.0%Not comparable
AA ITBenchSource —42.7%Not comparable
AA Tau3 BankingSource —26.8%Not comparable
terminalBenchHardSource —50.8%Not comparable
aaTerminalBench21Source —77.9%Not comparable
CodingClaude Opus 4.5 wins
BenchmarkClaude Opus 4.5GLM-5.2Result
SWE-bench VerifiedSource 80.9%—Not comparable
LiveCodeBench v6Source 84.8%—Not comparable
SWE-bench ProSource 57.1%62.1%GLM-5.2 leads
SWE MultilingualSource 77.5%—Not comparable
NL2RepoSource 43.2%48.9%GLM-5.2 leads
AA-SciCodeSource 47.0%50.5%GLM-5.2 leads
Terminal-Bench 2.0Source —81.0%Not comparable
ProgramBenchSource —63.7%Not comparable
cursorBench32Source —55.0%Not comparable
AA Coding IndexSource —68.8%Not comparable
Reasoning
BenchmarkClaude Opus 4.5GLM-5.2Result
LongBench v2Source 64.4%—Not comparable
AI-NeedleSource 74%—Not comparable
AA-LCRSource 65.3%71.3%GLM-5.2 leads
CritPtSource 0.3%20.9%GLM-5.2 leads
KnowledgeGLM-5.2 wins
BenchmarkClaude Opus 4.5GLM-5.2Result
GPQASource 87%91.2%GLM-5.2 leads
SuperGPQASource 70.6%—Not comparable
MMLU-ProSource 89.5%—Not comparable
MMLU-ReduxSource 96.6%—Not comparable
C-EvalSource 92.2%—Not comparable
HLESource 30.8%54.7%GLM-5.2 leads
Artificial Analysis Intelligence IndexSource 34.7%51.1%GLM-5.2 leads
AA-GPQA DiamondSource 81.0%89.5%GLM-5.2 leads
AA-HLESource 12.9%40.1%GLM-5.2 leads
AA-Omniscience IndexSource -3.9%4.0%GLM-5.2 leads
AA-Omniscience AccuracySource 40.7%25.1%Claude Opus 4.5 leads
AA-Omniscience Hallucination RateSource 75.4%28.1%GLM-5.2 leads
AA MMLU-ProSource 88.9%—Not comparable
GPQA-DSource —91.2%Not comparable
HLE w/o toolsSource —40.5%Not comparable
AA Openness IndexSource —44.4%Not comparable
MathGLM-5.2 wins
BenchmarkClaude Opus 4.5GLM-5.2Result
AIME26Source 95.1%99.2%GLM-5.2 leads
HMMT Feb 2025Source 92.9%—Not comparable
HMMT Nov 2025Source 93.3%94.4%GLM-5.2 leads
HMMT Feb 2026Source 85.3%92.5%GLM-5.2 leads
MMAnswerBenchSource 84.0%91.0%GLM-5.2 leads
FrontierMath v2 (Tiers 1-3)Source 20.690%—Not comparable
FrontierMath v2 (Tier 4)Source 4.167%—Not comparable
Multilingual
BenchmarkClaude Opus 4.5GLM-5.2Result
MMLU-ProXSource 85.7%—Not comparable
NOVA-63Source 56.7%—Not comparable
Multimodal
BenchmarkClaude Opus 4.5GLM-5.2Result
MMMU-ProSource 70.6%—Not comparable
MathVisionSource 74.3%—Not comparable
CharXivSource 68.5%—Not comparable
VideoMMMUSource 84.4%—Not comparable
ScreenSpot ProSource 45.7%—Not comparable
V*Source 67.0%—Not comparable
AA-MMMU-ProSource 71.2%—Not comparable
Design Arena WebsiteSource 12771340GLM-5.2 leads
Inst. Following
BenchmarkClaude Opus 4.5GLM-5.2Result
IFEvalSource 90.9%—Not comparable
IFBenchSource 58%—Not comparable
AA-IFBenchSource 43.0%73.3%GLM-5.2 leads
Frequently Asked Questions (5)

Which is better, Claude Opus 4.5 or GLM-5.2?

Claude Opus 4.5 is ahead on BenchLM's BenchAlign leaderboard, 64.22 to 63.96. The biggest single separator in this matchup is HLE, where the scores are 30.8% and 54.7%.

Which is better for knowledge tasks, Claude Opus 4.5 or GLM-5.2?

GLM-5.2 has the edge for knowledge tasks in this comparison, averaging 59.6 versus 58.1. Inside this category, AA-Omniscience Hallucination Rate is the benchmark that creates the most daylight between them.

Which is better for coding, Claude Opus 4.5 or GLM-5.2?

Claude Opus 4.5 has the edge for coding in this comparison, averaging 71.7 versus 62.1. Inside this category, NL2Repo is the benchmark that creates the most daylight between them.

Which is better for math, Claude Opus 4.5 or GLM-5.2?

GLM-5.2 has the edge for math in this comparison, averaging 95.9 versus 57.5. Inside this category, HMMT Feb 2026 is the benchmark that creates the most daylight between them.

Which is better for agentic tasks, Claude Opus 4.5 or GLM-5.2?

GLM-5.2 has the edge for agentic tasks in this comparison, averaging 81 versus 62.6. Inside this category, MCP Atlas is the benchmark that creates the most daylight between them.

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