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Model comparison

Claude Opus 4.8 vs GLM-5.2

Data verified

Head-to-head evidence from 34 shared benchmark results across 6 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.

78.34/100
Margin
14.4pts
← winning
63.96/100
2 category wins2 category wins

Public leaderboard positions: Claude Opus 4.8 #5 (Supported); GLM-5.2 #37 (Estimated). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.

Evidence parity. Claude Opus 4.8 and GLM-5.2 share 34 comparable benchmark results. 4 of 8 categories are comparable. 19 results are unique to Claude Opus 4.8; 9 to GLM-5.2.

Updated July 23, 2026
Shared results
34
Claude Opus 4.8 only
19
GLM-5.2 only
9
Comparable categories
4 / 8

Pick Claude Opus 4.8 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 34 shared benchmark results across 6 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 4.8 is clearly ahead on the BenchAlign aggregate, 78.34 to 63.96. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.

Claude Opus 4.8's sharpest advantage is in coding, where it averages 81.1 against 62.1. The single biggest benchmark swing on the page is SWE-bench Pro, 69.2% to 62.1%. 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 4.8 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.

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 4.8 and GLM-5.2
CategoryClaude Opus 4.8ΔGLM-5.2
MathClaude Opus 4.853.9Margin→ 42.0GLM-5.295.9
CodingClaude Opus 4.881.1Margin← 19.0GLM-5.262.1
KnowledgeClaude Opus 4.862.7Margin← 3.1GLM-5.259.6
AgenticClaude Opus 4.880.3Margin→ 0.7GLM-5.281.0
MultimodalClaude Opus 4.877.0MarginNo overlapGLM-5.2Not measured

Decisive benchmark drivers

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

More
A · Claude Opus 4.8B · GLM-5.2

  1. SWE-bench Pro

    Coding
    Source ↗
    A 69.2%B 62.1%
    Winner: Claude Opus 4.8Δ 7.1
    SWE-bench Pro: Claude Opus 4.8 scored 69.2%; GLM-5.2 scored 62.1%. Claude Opus 4.8 wins this benchmark.

  2. Terminal-Bench 2.0

    Agentic
    Source ↗
    A 74.6%B 81%
    Winner: GLM-5.2Δ 6.4
    Terminal-Bench 2.0: Claude Opus 4.8 scored 74.6%; GLM-5.2 scored 81%. GLM-5.2 wins this benchmark.

  3. HLE

    Knowledge
    Source ↗
    A 57.9%B 54.7%
    Winner: Claude Opus 4.8Δ 3.2
    HLE: Claude Opus 4.8 scored 57.9%; GLM-5.2 scored 54.7%. Claude Opus 4.8 wins this benchmark.

  4. GPQA

    Knowledge
    Source ↗
    A 93.6%B 91.2%
    Winner: Claude Opus 4.8Δ 2.4
    GPQA: Claude Opus 4.8 scored 93.6%; GLM-5.2 scored 91.2%. Claude Opus 4.8 wins this benchmark.

Operational comparison

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

MetricClaude Opus 4.8GLM-5.2Comparison
Input / output priceUSD per 1M tokensClaude Opus 4.8$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 4.8Not availableGLM-5.2Not availableA complete speed comparison is not available.
First-answer latencyseconds to first tokenClaude Opus 4.8Not availableGLM-5.2Not availableA complete latency comparison is not available.
Context windowmaximum listed tokensClaude Opus 4.81MGLM-5.21MListed context windows are equal.

Benchmark Deep Dive

AgenticGLM-5.2 wins
BenchmarkClaude Opus 4.8GLM-5.2Result
Terminal-Bench 2.0Source 74.6%81%GLM-5.2 leads
BrowseCompSource 84.3%—Not comparable
DeepSearchQASource 93.1%—Not comparable
OSWorld-VerifiedSource 83.4%—Not comparable
Finance Agent v2Source 53.9%—Not comparable
GDPval-AASource 15941514Claude Opus 4.8 leads
MCP AtlasSource 82.2%76.8%Claude Opus 4.8 leads
ToolathlonSource 59.9%48.2%Claude Opus 4.8 leads
Gert LabsSource 72.97%—Not comparable
AA Agentic IndexSource 47.2%43.1%Claude Opus 4.8 leads
τ²-bench resultsSource 94.4%99.1%GLM-5.2 leads
GDPval-AASource 54.7%50.7%Claude Opus 4.8 leads
ResearchClawBenchSource 21.1%20.7%Claude Opus 4.8 leads
OSWorld 2.0Source 20.6%—Not comparable
AA BriefcaseSource 13471260Claude Opus 4.8 leads
AA AutomationBenchSource 48.5%27.8%Claude Opus 4.8 leads
AA EnterpriseOps-GymSource 44.0%42.7%Claude Opus 4.8 leads
AA Harvey LABSource 91.1%91.0%Claude Opus 4.8 leads
AA Tau3 BankingSource 27.6%26.8%Claude Opus 4.8 leads
terminalBenchHardSource 58.3%50.8%Claude Opus 4.8 leads
aaTerminalBench21Source 84.6%77.9%Claude Opus 4.8 leads
APEX-Agents-AASource —33.7%Not comparable
AA ITBenchSource —42.7%Not comparable
CodingClaude Opus 4.8 wins
BenchmarkClaude Opus 4.8GLM-5.2Result
SWE-bench VerifiedSource 88.6%—Not comparable
SWE-bench ProSource 69.2%62.1%Claude Opus 4.8 leads
SWE MultilingualSource 84.4%—Not comparable
SWE MultimodalSource 38.4%—Not comparable
Terminal-Bench 2.0Source 74.6%81.0%GLM-5.2 leads
cursorBench31Source 58.4%—Not comparable
cursorBench32Source 62.3%55.0%Claude Opus 4.8 leads
AA Coding IndexSource 74.3%68.8%Claude Opus 4.8 leads
AA-SciCodeSource 53.5%50.5%Claude Opus 4.8 leads
FrontierCode 1.1 MainSource 46.5%—Not comparable
NL2RepoSource —48.9%Not comparable
ProgramBenchSource —63.7%Not comparable
Reasoning
BenchmarkClaude Opus 4.8GLM-5.2Result
AA-LCRSource 67.7%71.3%GLM-5.2 leads
CritPtSource 20.9%20.9%Tie
KnowledgeClaude Opus 4.8 wins
BenchmarkClaude Opus 4.8GLM-5.2Result
GPQASource 93.6%91.2%Claude Opus 4.8 leads
GPQA-DSource 93.6%91.2%Claude Opus 4.8 leads
HLESource 57.9%54.7%Claude Opus 4.8 leads
HLE w/o toolsSource 49.8%40.5%Claude Opus 4.8 leads
Artificial Analysis Intelligence IndexSource 55.7%51.1%Claude Opus 4.8 leads
AA-GPQA DiamondSource 92.0%89.5%Claude Opus 4.8 leads
AA-HLESource 45.7%40.1%Claude Opus 4.8 leads
AA-Omniscience IndexSource 27.4%4.0%Claude Opus 4.8 leads
AA-Omniscience AccuracySource 46.6%25.1%Claude Opus 4.8 leads
AA-Omniscience Hallucination RateSource 35.9%28.1%GLM-5.2 leads
AA Openness IndexSource —44.4%Not comparable
MathGLM-5.2 wins
BenchmarkClaude Opus 4.8GLM-5.2Result
USAMO 2026Source 96.7%—Not comparable
FrontierMath v2 (Tiers 1-3)Source 47.241%—Not comparable
FrontierMath v2 (Tier 4)Source 31.250%—Not comparable
AIME26Source —99.2%Not comparable
HMMT Nov 2025Source —94.4%Not comparable
HMMT Feb 2026Source —92.5%Not comparable
MMAnswerBenchSource —91.0%Not comparable
Multilingual
BenchmarkClaude Opus 4.8GLM-5.2Result
INCLUDESource 87.6%—Not comparable
Multimodal
BenchmarkClaude Opus 4.8GLM-5.2Result
OfficeQA ProSource 66.2%—Not comparable
ScreenSpot ProSource 87.9%—Not comparable
CharXivSource 89.9%—Not comparable
CharXiv w/o toolsSource 80.5%—Not comparable
Design Arena WebsiteSource 12701340GLM-5.2 leads
Inst. Following
BenchmarkClaude Opus 4.8GLM-5.2Result
AA-IFBenchSource 62.2%73.3%GLM-5.2 leads
Frequently Asked Questions (5)

Which is better, Claude Opus 4.8 or GLM-5.2?

Claude Opus 4.8 is ahead on BenchLM's BenchAlign leaderboard, 78.34 to 63.96. The biggest single separator in this matchup is SWE-bench Pro, where the scores are 69.2% and 62.1%.

Which is better for knowledge tasks, Claude Opus 4.8 or GLM-5.2?

Claude Opus 4.8 has the edge for knowledge tasks in this comparison, averaging 62.7 versus 59.6. Inside this category, AA-Omniscience Index is the benchmark that creates the most daylight between them.

Which is better for coding, Claude Opus 4.8 or GLM-5.2?

Claude Opus 4.8 has the edge for coding in this comparison, averaging 81.1 versus 62.1. Inside this category, cursorBench32 is the benchmark that creates the most daylight between them.

Which is better for math, Claude Opus 4.8 or GLM-5.2?

GLM-5.2 has the edge for math in this comparison, averaging 95.9 versus 53.9. Claude Opus 4.8 stays close enough that the answer can still flip depending on your workload.

Which is better for agentic tasks, Claude Opus 4.8 or GLM-5.2?

GLM-5.2 has the edge for agentic tasks in this comparison, averaging 81 versus 80.3. Inside this category, AA Briefcase is the benchmark that creates the most daylight between them.

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