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Model comparison

Claude Opus 4.5 vs GLM-4.7

Data verified

Head-to-head evidence from 21 shared benchmark results across 7 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.

64.22/100
Margin
3.1pts
← winning
61.16/100
3 category wins1 category wins

Public leaderboard positions: Claude Opus 4.5 #34 (Supported); GLM-4.7 #42 (Supported). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.

Evidence parity. Claude Opus 4.5 and GLM-4.7 share 21 comparable benchmark results. 4 of 8 categories are comparable. 38 results are unique to Claude Opus 4.5; 9 to GLM-4.7.

Updated July 20, 2026
Shared results
21
Claude Opus 4.5 only
38
GLM-4.7 only
9
Comparable categories
4 / 8

Pick Claude Opus 4.5 if you want the stronger benchmark profile. GLM-4.7 only becomes the better choice if coding is the priority or you want the cheaper token bill.

Confidence note. This is a partial-evidence comparison with 21 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 is clearly ahead on the BenchAlign aggregate, 64.22 to 61.16. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.

Claude Opus 4.5's sharpest advantage is in mathematics, where it averages 57.5 against 1.8. The single biggest benchmark swing on the page is Terminal-Bench 2.0, 59.3% to 41%. GLM-4.7 does hit back in coding, 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 $0.00 input / $0.00 output per 1M tokens for GLM-4.7. That is roughly Infinityx on output cost alone. GLM-4.7 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.

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-4.7
CategoryClaude Opus 4.5ΔGLM-4.7
MathClaude Opus 4.557.5Margin← 55.7GLM-4.71.8
AgenticClaude Opus 4.562.6Margin← 16.9GLM-4.745.7
KnowledgeClaude Opus 4.558.1Margin← 6.3GLM-4.751.8
CodingClaude Opus 4.571.7Margin→ 3.7GLM-4.775.4
ReasoningClaude Opus 4.564.4MarginNo overlapGLM-4.7Not measured
MultilingualClaude Opus 4.585.7MarginNo overlapGLM-4.7Not measured
MultimodalClaude Opus 4.569.9MarginNo overlapGLM-4.7Not measured
Inst. FollowingClaude Opus 4.569.5MarginNo overlapGLM-4.7Not measured

Decisive benchmark drivers

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

More
A · Claude Opus 4.5B · GLM-4.7

  1. Terminal-Bench 2.0

    Agentic
    Source ↗
    A 59.3%B 41%
    Winner: Claude Opus 4.5Δ 18.3
    Terminal-Bench 2.0: Claude Opus 4.5 scored 59.3%; GLM-4.7 scored 41%. Claude Opus 4.5 wins this benchmark.

  2. FrontierMath v2 (Tiers 1-3)

    Math
    Source ↗
    A 20.690%B 2.439%
    Winner: Claude Opus 4.5Δ 18.3
    FrontierMath v2 (Tiers 1-3): Claude Opus 4.5 scored 20.690%; GLM-4.7 scored 2.439%. Claude Opus 4.5 wins this benchmark.

  3. SWE-bench Verified

    Coding
    Source ↗
    A 80.9%B 73.8%
    Winner: Claude Opus 4.5Δ 7.1
    SWE-bench Verified: Claude Opus 4.5 scored 80.9%; GLM-4.7 scored 73.8%. Claude Opus 4.5 wins this benchmark.

  4. HLE

    Knowledge
    Source ↗
    A 30.8%B 24.8%
    Winner: Claude Opus 4.5Δ 6
    HLE: Claude Opus 4.5 scored 30.8%; GLM-4.7 scored 24.8%. Claude Opus 4.5 wins this benchmark.

  5. MMLU-Pro

    Knowledge
    Source ↗
    A 89.5%B 84.3%
    Winner: Claude Opus 4.5Δ 5.2
    MMLU-Pro: Claude Opus 4.5 scored 89.5%; GLM-4.7 scored 84.3%. Claude Opus 4.5 wins this benchmark.

Operational comparison

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

MetricClaude Opus 4.5GLM-4.7Comparison
Input / output priceUSD per 1M tokensClaude Opus 4.5$5 input / $25 outputGLM-4.7$0 input / $0 outputGLM-4.7 has the lower combined listed price.
Generation speedtokens per secondClaude Opus 4.546 tok/sGLM-4.782 tok/sGLM-4.7 has the higher measured throughput.
First-answer latencyseconds to first tokenClaude Opus 4.51.01 sGLM-4.71.10 sClaude Opus 4.5 reaches the first token sooner.
Context windowmaximum listed tokensClaude Opus 4.5200KGLM-4.7200KListed context windows are equal.

Benchmark Deep Dive

AgenticClaude Opus 4.5 wins
BenchmarkClaude Opus 4.5GLM-4.7Result
Terminal-Bench 2.0Source 59.3%41%Claude Opus 4.5 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%15.5%Claude Opus 4.5 leads
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%95.9%GLM-4.7 leads
Gert LabsSource 64.23%39.95%Claude Opus 4.5 leads
JobBenchSource 32.3%—Not comparable
BrowseCompSource —52%Not comparable
AA Agentic IndexSource —25.4%Not comparable
GDPval-AASource —33.3%Not comparable
GDPval-AASource —1165Not comparable
CodingGLM-4.7 wins
BenchmarkClaude Opus 4.5GLM-4.7Result
SWE-bench VerifiedSource 80.9%73.8%Claude Opus 4.5 leads
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%45.1%Claude Opus 4.5 leads
LiveCodeBenchSource —84.9%Not comparable
SWE-RebenchSource —58.7%Not comparable
AA Coding IndexSource —45.3%Not comparable
AA LiveCodeBenchSource —89.4%Not comparable
Reasoning
BenchmarkClaude Opus 4.5GLM-4.7Result
LongBench v2Source 64.4%—Not comparable
AI-NeedleSource 74%—Not comparable
AA-LCRSource 65.3%64.0%Claude Opus 4.5 leads
CritPtSource 0.3%1.7%GLM-4.7 leads
KnowledgeClaude Opus 4.5 wins
BenchmarkClaude Opus 4.5GLM-4.7Result
GPQASource 87%85.7%Claude Opus 4.5 leads
SuperGPQASource 70.6%—Not comparable
MMLU-ProSource 89.5%84.3%Claude Opus 4.5 leads
MMLU-ReduxSource 96.6%—Not comparable
C-EvalSource 92.2%—Not comparable
HLESource 30.8%24.8%Claude Opus 4.5 leads
Artificial Analysis Intelligence IndexSource 34.7%33.7%Claude Opus 4.5 leads
AA-GPQA DiamondSource 81.0%85.9%GLM-4.7 leads
AA-HLESource 12.9%25.1%GLM-4.7 leads
AA-Omniscience IndexSource -3.9%-34.6%Claude Opus 4.5 leads
AA-Omniscience AccuracySource 40.7%29.3%Claude Opus 4.5 leads
AA-Omniscience Hallucination RateSource 75.4%90.3%Claude Opus 4.5 leads
AA MMLU-ProSource 88.9%—Not comparable
MathClaude Opus 4.5 wins
BenchmarkClaude Opus 4.5GLM-4.7Result
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%2.439%Claude Opus 4.5 leads
FrontierMath v2 (Tier 4)Source 4.167%0.000%Claude Opus 4.5 leads
AIME 2025Source —95.7%Not comparable
Multilingual
BenchmarkClaude Opus 4.5GLM-4.7Result
MMLU-ProXSource 85.7%—Not comparable
NOVA-63Source 56.7%—Not comparable
Multimodal
BenchmarkClaude Opus 4.5GLM-4.7Result
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 12791258Claude Opus 4.5 leads
Inst. Following
BenchmarkClaude Opus 4.5GLM-4.7Result
IFEvalSource 90.9%—Not comparable
IFBenchSource 58%—Not comparable
AA-IFBenchSource 43.0%67.9%GLM-4.7 leads
Frequently Asked Questions (5)

Which is better, Claude Opus 4.5 or GLM-4.7?

Claude Opus 4.5 is ahead on BenchLM's BenchAlign leaderboard, 64.22 to 61.16. The biggest single separator in this matchup is Terminal-Bench 2.0, where the scores are 59.3% and 41%.

Which is better for knowledge tasks, Claude Opus 4.5 or GLM-4.7?

Claude Opus 4.5 has the edge for knowledge tasks in this comparison, averaging 58.1 versus 51.8. Inside this category, AA-Omniscience Index is the benchmark that creates the most daylight between them.

Which is better for coding, Claude Opus 4.5 or GLM-4.7?

GLM-4.7 has the edge for coding in this comparison, averaging 75.4 versus 71.7. Inside this category, SWE-bench Verified is the benchmark that creates the most daylight between them.

Which is better for math, Claude Opus 4.5 or GLM-4.7?

Claude Opus 4.5 has the edge for math in this comparison, averaging 57.5 versus 1.8. Inside this category, FrontierMath v2 (Tiers 1-3) is the benchmark that creates the most daylight between them.

Which is better for agentic tasks, Claude Opus 4.5 or GLM-4.7?

Claude Opus 4.5 has the edge for agentic tasks in this comparison, averaging 62.6 versus 45.7. Inside this category, Gert Labs is the benchmark that creates the most daylight between them.

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