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Model comparison

Claude Opus 4.5 vs GLM-5

Data verified

Head-to-head evidence from 42 shared benchmark results across 8 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.

64.22/100
Margin
1.8pts
winning →
GLM-5
Z.AI
66.06/100
5 category wins2 category wins

Public leaderboard positions: Claude Opus 4.5 #34 (Supported); GLM-5 #28 (Supported). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.

Evidence parity. Claude Opus 4.5 and GLM-5 share 42 comparable benchmark results. 7 of 8 categories are comparable. 17 results are unique to Claude Opus 4.5; 7 to GLM-5.

Updated July 22, 2026
Shared results
42
Claude Opus 4.5 only
17
GLM-5 only
7
Comparable categories
7 / 8

Pick GLM-5 if you want the stronger benchmark profile. Claude Opus 4.5 only becomes the better choice if agentic is the priority.

Confidence note. This is a partial-evidence comparison with 42 shared benchmark results across 8 evidence categories; 7 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.

Why this result

GLM-5 has the cleaner BenchAlign overall profile here, landing at 66.06 versus 64.22. It is a real lead, but still close enough that category-level strengths matter more than the headline number.

GLM-5's sharpest advantage is in instruction following, where it averages 92.6 against 69.5. The single biggest benchmark swing on the page is HLE, 30.8% to 50.4%. Claude Opus 4.5 does hit back in agentic, 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 $1.00 input / $3.20 output per 1M tokens for GLM-5. That is roughly 7.8x 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 4.5 and GLM-5
CategoryClaude Opus 4.5ΔGLM-5
Inst. FollowingClaude Opus 4.569.5Margin→ 23.1GLM-592.6
KnowledgeClaude Opus 4.558.1Margin→ 8.3GLM-566.4
AgenticClaude Opus 4.562.6Margin← 6.4GLM-556.2
CodingClaude Opus 4.571.7Margin← 5.4GLM-566.3
ReasoningClaude Opus 4.564.4Margin← 3.6GLM-560.8
MultilingualClaude Opus 4.585.7Margin← 2.6GLM-583.1
MathClaude Opus 4.557.5Margin← 1.2GLM-556.3
MultimodalClaude Opus 4.569.9MarginNo overlapGLM-5Not measured

Decisive benchmark drivers

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

More
A · Claude Opus 4.5B · GLM-5

  1. HLE

    Knowledge
    Source ↗
    A 30.8%B 50.4%
    Winner: GLM-5Δ 19.6
    HLE: Claude Opus 4.5 scored 30.8%; GLM-5 scored 50.4%. GLM-5 wins this benchmark.

  2. FrontierMath v2 (Tiers 1-3)

    Math
    Source ↗
    A 20.690%B 16.434%
    Winner: Claude Opus 4.5Δ 4.3
    FrontierMath v2 (Tiers 1-3): Claude Opus 4.5 scored 20.690%; GLM-5 scored 16.434%. Claude Opus 4.5 wins this benchmark.

  3. SuperGPQA

    Knowledge
    Source ↗
    A 70.6%B 66.8%
    Winner: Claude Opus 4.5Δ 3.8
    SuperGPQA: Claude Opus 4.5 scored 70.6%; GLM-5 scored 66.8%. Claude Opus 4.5 wins this benchmark.

  4. MMLU-Pro

    Knowledge
    Source ↗
    A 89.5%B 85.7%
    Winner: Claude Opus 4.5Δ 3.8
    MMLU-Pro: Claude Opus 4.5 scored 89.5%; GLM-5 scored 85.7%. Claude Opus 4.5 wins this benchmark.

  5. LongBench v2

    Reasoning
    Source ↗
    A 64.4%B 60.8%
    Winner: Claude Opus 4.5Δ 3.6
    LongBench v2: Claude Opus 4.5 scored 64.4%; GLM-5 scored 60.8%. 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-5Comparison
Input / output priceUSD per 1M tokensClaude Opus 4.5$5 input / $25 outputGLM-5$1 input / $3.2 outputGLM-5 has the lower combined listed price.
Generation speedtokens per secondClaude Opus 4.546 tok/sGLM-574 tok/sGLM-5 has the higher measured throughput.
First-answer latencyseconds to first tokenClaude Opus 4.51.01 sGLM-51.64 sClaude Opus 4.5 reaches the first token sooner.
Context windowmaximum listed tokensClaude Opus 4.5200KGLM-5200KListed context windows are equal.

Benchmark Deep Dive

AgenticClaude Opus 4.5 wins
BenchmarkClaude Opus 4.5GLM-5Result
Terminal-Bench 2.0Source 59.3%56.2%Claude Opus 4.5 leads
OSWorld-VerifiedSource 66.3%—Not comparable
OSWorldSource 66.3%—Not comparable
Claw-EvalSource 59.6%57.7%Claude Opus 4.5 leads
QwenClawBenchSource 52.3%54.1%GLM-5 leads
τ³-bench resultsSource 70.2%65.6%Claude Opus 4.5 leads
VITA-BenchSource 23.3%—Not comparable
DeepPlanningSource 26.4%14.6%Claude Opus 4.5 leads
ToolathlonSource 43.5%38%Claude Opus 4.5 leads
MCP AtlasSource 42.3%31.1%Claude Opus 4.5 leads
MCP-TasksSource 71.8%60.8%Claude Opus 4.5 leads
WideResearchSource 76.4%69.8%Claude Opus 4.5 leads
CyberGymSource 50.6%43.2%Claude Opus 4.5 leads
τ²-bench resultsSource 86.3%98.2%GLM-5 leads
Gert LabsSource 64.23%50.99%Claude Opus 4.5 leads
JobBenchSource 32.3%—Not comparable
APEX-Agents-AASource —14.5%Not comparable
CodingClaude Opus 4.5 wins
BenchmarkClaude Opus 4.5GLM-5Result
SWE-bench VerifiedSource 80.9%77.8%Claude Opus 4.5 leads
LiveCodeBench v6Source 84.8%—Not comparable
SWE-bench ProSource 57.1%55.1%Claude Opus 4.5 leads
SWE MultilingualSource 77.5%73.3%Claude Opus 4.5 leads
NL2RepoSource 43.2%—Not comparable
AA-SciCodeSource 47.0%46.2%Claude Opus 4.5 leads
SWE-bench Verified*Source —72.8%Not comparable
SWE-RebenchSource —62.8%Not comparable
React Native EvalsSource —74.8%Not comparable
ReasoningClaude Opus 4.5 wins
BenchmarkClaude Opus 4.5GLM-5Result
LongBench v2Source 64.4%60.8%Claude Opus 4.5 leads
AI-NeedleSource 74%63.3%Claude Opus 4.5 leads
AA-LCRSource 65.3%63.3%Claude Opus 4.5 leads
CritPtSource 0.3%2.0%GLM-5 leads
KnowledgeGLM-5 wins
BenchmarkClaude Opus 4.5GLM-5Result
GPQASource 87%86%Claude Opus 4.5 leads
SuperGPQASource 70.6%66.8%Claude Opus 4.5 leads
MMLU-ProSource 89.5%85.7%Claude Opus 4.5 leads
MMLU-ReduxSource 96.6%—Not comparable
C-EvalSource 92.2%—Not comparable
HLESource 30.8%50.4%GLM-5 leads
Artificial Analysis Intelligence IndexSource 34.7%39.5%GLM-5 leads
AA-GPQA DiamondSource 81.0%82.0%GLM-5 leads
AA-HLESource 12.9%27.2%GLM-5 leads
AA-Omniscience IndexSource -3.9%2.0%GLM-5 leads
AA-Omniscience AccuracySource 40.7%26.9%Claude Opus 4.5 leads
AA-Omniscience Hallucination RateSource 75.4%34.0%GLM-5 leads
AA MMLU-ProSource 88.9%—Not comparable
GPQA-DSource —86.0%Not comparable
MMLU-Pro (Arcee)Source —85.8%Not comparable
MathClaude Opus 4.5 wins
BenchmarkClaude Opus 4.5GLM-5Result
AIME26Source 95.1%95.8%GLM-5 leads
HMMT Feb 2025Source 92.9%97.5%GLM-5 leads
HMMT Nov 2025Source 93.3%96.9%GLM-5 leads
HMMT Feb 2026Source 85.3%86.4%GLM-5 leads
MMAnswerBenchSource 84.0%82.5%Claude Opus 4.5 leads
FrontierMath v2 (Tiers 1-3)Source 20.690%16.434%Claude Opus 4.5 leads
FrontierMath v2 (Tier 4)Source 4.167%2.100%Claude Opus 4.5 leads
AIME25 (Arcee)Source —93.3%Not comparable
MultilingualClaude Opus 4.5 wins
BenchmarkClaude Opus 4.5GLM-5Result
MMLU-ProXSource 85.7%83.1%Claude Opus 4.5 leads
NOVA-63Source 56.7%55.1%Claude Opus 4.5 leads
Multimodal
BenchmarkClaude Opus 4.5GLM-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 12771278GLM-5 leads
Inst. FollowingGLM-5 wins
BenchmarkClaude Opus 4.5GLM-5Result
IFEvalSource 90.9%92.6%GLM-5 leads
IFBenchSource 58%—Not comparable
AA-IFBenchSource 43.0%72.3%GLM-5 leads
Frequently Asked Questions (8)

Which is better, Claude Opus 4.5 or GLM-5?

GLM-5 is ahead on BenchLM's BenchAlign leaderboard, 66.06 to 64.22. The biggest single separator in this matchup is HLE, where the scores are 30.8% and 50.4%.

Which is better for knowledge tasks, Claude Opus 4.5 or GLM-5?

GLM-5 has the edge for knowledge tasks in this comparison, averaging 66.4 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?

Claude Opus 4.5 has the edge for coding in this comparison, averaging 71.7 versus 66.3. Inside this category, SWE Multilingual is the benchmark that creates the most daylight between them.

Which is better for math, Claude Opus 4.5 or GLM-5?

Claude Opus 4.5 has the edge for math in this comparison, averaging 57.5 versus 56.3. Inside this category, HMMT Feb 2025 is the benchmark that creates the most daylight between them.

Which is better for reasoning, Claude Opus 4.5 or GLM-5?

Claude Opus 4.5 has the edge for reasoning in this comparison, averaging 64.4 versus 60.8. Inside this category, AI-Needle is the benchmark that creates the most daylight between them.

Which is better for agentic tasks, Claude Opus 4.5 or GLM-5?

Claude Opus 4.5 has the edge for agentic tasks in this comparison, averaging 62.6 versus 56.2. Inside this category, Gert Labs is the benchmark that creates the most daylight between them.

Which is better for instruction following, Claude Opus 4.5 or GLM-5?

GLM-5 has the edge for instruction following in this comparison, averaging 92.6 versus 69.5. Inside this category, AA-IFBench is the benchmark that creates the most daylight between them.

Which is better for multilingual tasks, Claude Opus 4.5 or GLM-5?

Claude Opus 4.5 has the edge for multilingual tasks in this comparison, averaging 85.7 versus 83.1. Inside this category, MMLU-ProX is the benchmark that creates the most daylight between them.

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