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Model comparison

Claude Opus 4.5 vs GLM-4.5

Data verified

Head-to-head evidence from 1 shared benchmark result across 1 category. Overall scores shown here use the public BenchAlign v5 ranking lane.

64.22/100
Margin
6.7pts
← winning
57.56/100
0 category wins0 category wins

Public leaderboard positions: Claude Opus 4.5 #34 (Supported); GLM-4.5 #68 (Estimated). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.

Evidence parity. Claude Opus 4.5 and GLM-4.5 share 1 comparable benchmark result. 0 of 8 categories are comparable. 58 results are unique to Claude Opus 4.5; 0 to GLM-4.5.

Updated July 20, 2026
Shared results
1
Claude Opus 4.5 only
58
GLM-4.5 only
0
Comparable categories
0 / 8

Benchmark data for Claude Opus 4.5 and GLM-4.5 is coming soon on BenchLM.

Confidence note. This is a partial-evidence comparison with 1 shared benchmark result across 1 evidence category; 0 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.

Why this result

BenchLM has partial data for these models, but not enough overlapping benchmark coverage to produce a fair score-level comparison yet.

Claude Opus 4.5 is priced at $5.00 input / $25.00 output per 1M tokens, versus $0.60 input / $2.20 output per 1M tokens for GLM-4.5. Claude Opus 4.5 has the larger context window at 200K, compared with 128K for GLM-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-4.5
CategoryClaude Opus 4.5ΔGLM-4.5
AgenticClaude Opus 4.562.6MarginNo overlapGLM-4.5Not measured
CodingClaude Opus 4.571.7MarginNo overlapGLM-4.5Not measured
ReasoningClaude Opus 4.564.4MarginNo overlapGLM-4.5Not measured
KnowledgeClaude Opus 4.558.1MarginNo overlapGLM-4.5Not measured
MathClaude Opus 4.557.5MarginNo overlapGLM-4.5Not measured
MultilingualClaude Opus 4.585.7MarginNo overlapGLM-4.5Not measured
MultimodalClaude Opus 4.569.9MarginNo overlapGLM-4.5Not measured
Inst. FollowingClaude Opus 4.569.5MarginNo overlapGLM-4.5Not measured

Operational comparison

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

MetricClaude Opus 4.5GLM-4.5Comparison
Input / output priceUSD per 1M tokensClaude Opus 4.5$5 input / $25 outputGLM-4.5$0.6 input / $2.2 outputGLM-4.5 has the lower combined listed price.
Generation speedtokens per secondClaude Opus 4.546 tok/sGLM-4.551 tok/sGLM-4.5 has the higher measured throughput.
First-answer latencyseconds to first tokenClaude Opus 4.51.01 sGLM-4.51.45 sClaude Opus 4.5 reaches the first token sooner.
Context windowmaximum listed tokensClaude Opus 4.5200KGLM-4.5128KClaude Opus 4.5 lists the larger context window.

Benchmark Deep Dive

Agentic
BenchmarkClaude Opus 4.5GLM-4.5Result
Terminal-Bench 2.0Source 59.3%—Not comparable
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%—Not comparable
MCP AtlasSource 42.3%—Not comparable
MCP-TasksSource 71.8%—Not comparable
WideResearchSource 76.4%—Not comparable
CyberGymSource 50.6%—Not comparable
τ²-bench resultsSource 86.3%—Not comparable
Gert LabsSource 64.23%—Not comparable
JobBenchSource 32.3%—Not comparable
Coding
BenchmarkClaude Opus 4.5GLM-4.5Result
SWE-bench VerifiedSource 80.9%—Not comparable
LiveCodeBench v6Source 84.8%—Not comparable
SWE-bench ProSource 57.1%—Not comparable
SWE MultilingualSource 77.5%—Not comparable
NL2RepoSource 43.2%—Not comparable
AA-SciCodeSource 47.0%—Not comparable
Reasoning
BenchmarkClaude Opus 4.5GLM-4.5Result
LongBench v2Source 64.4%—Not comparable
AI-NeedleSource 74%—Not comparable
AA-LCRSource 65.3%—Not comparable
CritPtSource 0.3%—Not comparable
Knowledge
BenchmarkClaude Opus 4.5GLM-4.5Result
GPQASource 87%—Not comparable
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%—Not comparable
Artificial Analysis Intelligence IndexSource 34.7%—Not comparable
AA-GPQA DiamondSource 81.0%—Not comparable
AA-HLESource 12.9%—Not comparable
AA-Omniscience IndexSource -3.9%—Not comparable
AA-Omniscience AccuracySource 40.7%—Not comparable
AA-Omniscience Hallucination RateSource 75.4%—Not comparable
AA MMLU-ProSource 88.9%—Not comparable
Math
BenchmarkClaude Opus 4.5GLM-4.5Result
AIME26Source 95.1%—Not comparable
HMMT Feb 2025Source 92.9%—Not comparable
HMMT Nov 2025Source 93.3%—Not comparable
HMMT Feb 2026Source 85.3%—Not comparable
MMAnswerBenchSource 84.0%—Not comparable
FrontierMath v2 (Tiers 1-3)Source 20.690%—Not comparable
FrontierMath v2 (Tier 4)Source 4.167%—Not comparable
Multilingual
BenchmarkClaude Opus 4.5GLM-4.5Result
MMLU-ProXSource 85.7%—Not comparable
NOVA-63Source 56.7%—Not comparable
Multimodal
BenchmarkClaude Opus 4.5GLM-4.5Result
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 12791202Claude Opus 4.5 leads
Inst. Following
BenchmarkClaude Opus 4.5GLM-4.5Result
IFEvalSource 90.9%—Not comparable
IFBenchSource 58%—Not comparable
AA-IFBenchSource 43.0%—Not comparable
Frequently Asked Questions (3)

Can I compare Claude Opus 4.5 and GLM-4.5 on BenchLM yet?

Not fully yet. BenchLM is tracking both models, but the sourced benchmark breakdown for this comparison is still coming soon.

Why does this comparison show “coming soon”?

BenchLM only shows category winners and benchmark-level calls when we have sourced results that can be compared fairly. For these models, the public benchmark coverage is not complete enough yet.

What data is available for Claude Opus 4.5 and GLM-4.5 today?

Claude Opus 4.5: $5.00 input / $25.00 output per 1M tokens GLM-4.5: $0.60 input / $2.20 output per 1M tokens Both model pages still include creator, context window, reasoning mode, and other metadata while benchmark coverage fills in.

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Last updated: July 20, 2026

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