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Model comparison

Claude Opus 4.6 vs GLM-5

Data verified

Head-to-head evidence from 30 shared benchmark results across 7 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.

68.59/100
Margin
2.5pts
← winning
GLM-5
Z.AI
66.06/100
3 category wins1 category wins

Public leaderboard positions: Claude Opus 4.6 #16 (Supported); GLM-5 #28 (Supported). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.

Evidence parity. Claude Opus 4.6 and GLM-5 share 30 comparable benchmark results. 4 of 8 categories are comparable. 16 results are unique to Claude Opus 4.6; 19 to GLM-5.

Updated July 20, 2026
Shared results
30
Claude Opus 4.6 only
16
GLM-5 only
19
Comparable categories
4 / 8

Pick Claude Opus 4.6 if you want the stronger benchmark profile. GLM-5 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 30 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 4.6 has the cleaner BenchAlign overall profile here, landing at 68.59 versus 66.06. It is a real lead, but still close enough that category-level strengths matter more than the headline number.

Claude Opus 4.6's sharpest advantage is in agentic, where it averages 73 against 56.2. The single biggest benchmark swing on the page is SuperGPQA, 95% to 66.8%. GLM-5 does hit back in mathematics, so the answer changes if that is the part of the workload you care about most.

Claude Opus 4.6 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. Claude Opus 4.6 gives you the larger context window at 1M, compared with 200K for GLM-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 4.6 and GLM-5
CategoryClaude Opus 4.6ΔGLM-5
MathClaude Opus 4.636.3Margin→ 20.0GLM-556.3
AgenticClaude Opus 4.673.0Margin← 16.8GLM-556.2
KnowledgeClaude Opus 4.669.1Margin← 2.7GLM-566.4
CodingClaude Opus 4.668.1Margin← 1.8GLM-566.3
ReasoningClaude Opus 4.6Not measuredMarginNo overlapGLM-560.8
MultilingualClaude Opus 4.6Not measuredMarginNo overlapGLM-583.1
MultimodalClaude Opus 4.677.3MarginNo overlapGLM-5Not measured
Inst. FollowingClaude Opus 4.6Not measuredMarginNo overlapGLM-592.6

Decisive benchmark drivers

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

More
A · Claude Opus 4.6B · GLM-5

  1. SuperGPQA

    Knowledge
    Source ↗
    A 95%B 66.8%
    Winner: Claude Opus 4.6Δ 28.2
    SuperGPQA: Claude Opus 4.6 scored 95%; GLM-5 scored 66.8%. Claude Opus 4.6 wins this benchmark.

  2. FrontierMath v2 (Tiers 1-3)

    Math
    Source ↗
    A 40.700%B 16.434%
    Winner: Claude Opus 4.6Δ 24.3
    FrontierMath v2 (Tiers 1-3): Claude Opus 4.6 scored 40.700%; GLM-5 scored 16.434%. Claude Opus 4.6 wins this benchmark.

  3. FrontierMath v2 (Tier 4)

    Math
    Source ↗
    A 22.900%B 2.100%
    Winner: Claude Opus 4.6Δ 20.8
    FrontierMath v2 (Tier 4): Claude Opus 4.6 scored 22.900%; GLM-5 scored 2.100%. Claude Opus 4.6 wins this benchmark.

  4. Terminal-Bench 2.0

    Agentic
    Source ↗
    A 65.4%B 56.2%
    Winner: Claude Opus 4.6Δ 9.2
    Terminal-Bench 2.0: Claude Opus 4.6 scored 65.4%; GLM-5 scored 56.2%. Claude Opus 4.6 wins this benchmark.

  5. GPQA

    Knowledge
    Source ↗
    A 91.3%B 86%
    Winner: Claude Opus 4.6Δ 5.3
    GPQA: Claude Opus 4.6 scored 91.3%; GLM-5 scored 86%. Claude Opus 4.6 wins this benchmark.

Operational comparison

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

MetricClaude Opus 4.6GLM-5Comparison
Input / output priceUSD per 1M tokensClaude Opus 4.6$5 input / $25 outputGLM-5$1 input / $3.2 outputGLM-5 has the lower combined listed price.
Generation speedtokens per secondClaude Opus 4.640 tok/sGLM-574 tok/sGLM-5 has the higher measured throughput.
First-answer latencyseconds to first tokenClaude Opus 4.61.78 sGLM-51.64 sGLM-5 reaches the first token sooner.
Context windowmaximum listed tokensClaude Opus 4.61MGLM-5200KClaude Opus 4.6 lists the larger context window.

Benchmark Deep Dive

AgenticClaude Opus 4.6 wins
BenchmarkClaude Opus 4.6GLM-5Result
Terminal-Bench 2.0Source 65.4%56.2%Claude Opus 4.6 leads
BrowseCompSource 83.7%—Not comparable
OSWorld-VerifiedSource 72.7%—Not comparable
τ²-bench resultsSource 84.8%98.2%GLM-5 leads
Claw-EvalSource 70.4%57.7%Claude Opus 4.6 leads
DeepSearchQASource 73.7%—Not comparable
CyberGymSource 66.6%43.2%Claude Opus 4.6 leads
Gert LabsSource 61.85%50.99%Claude Opus 4.6 leads
ResearchClawBenchSource 19.9%—Not comparable
JobBenchSource 36.7%—Not comparable
QwenClawBenchSource —54.1%Not comparable
τ³-bench resultsSource —65.6%Not comparable
DeepPlanningSource —14.6%Not comparable
ToolathlonSource —38%Not comparable
MCP AtlasSource —31.1%Not comparable
MCP-TasksSource —60.8%Not comparable
WideResearchSource —69.8%Not comparable
APEX-Agents-AASource —14.5%Not comparable
CodingClaude Opus 4.6 wins
BenchmarkClaude Opus 4.6GLM-5Result
SWE-bench VerifiedSource 80.8%77.8%Claude Opus 4.6 leads
SWE-bench Verified*Source 75.6%72.8%Claude Opus 4.6 leads
LiveCodeBench ProSource 70.7%—Not comparable
SWE-bench ProSource 53.4%55.1%GLM-5 leads
SWE-RebenchSource 65.3%62.8%Claude Opus 4.6 leads
React Native EvalsSource 84.1%74.8%Claude Opus 4.6 leads
Vibe Code BenchSource 57.57%—Not comparable
AA-SciCodeSource 45.7%46.2%GLM-5 leads
FrontierCode 1.1 MainSource 26.9%—Not comparable
SWE MultilingualSource —73.3%Not comparable
Reasoning
BenchmarkClaude Opus 4.6GLM-5Result
AA-LCRSource 58.3%63.3%GLM-5 leads
CritPtSource 2.8%2.0%Claude Opus 4.6 leads
LongBench v2Source —60.8%Not comparable
AI-NeedleSource —63.3%Not comparable
KnowledgeClaude Opus 4.6 wins
BenchmarkClaude Opus 4.6GLM-5Result
GPQASource 91.3%86%Claude Opus 4.6 leads
GPQA-DSource 89.2%86.0%Claude Opus 4.6 leads
SuperGPQASource 95%66.8%Claude Opus 4.6 leads
MMLU-ProSource 82%85.7%GLM-5 leads
MMLU-Pro (Arcee)Source 89.1%85.8%Claude Opus 4.6 leads
HLESource 53%50.4%Claude Opus 4.6 leads
HLE w/o toolsSource 40%—Not comparable
HealthBench HardSource 14.8%—Not comparable
MedXpertQA (Text)Source 52.1%—Not comparable
Artificial Analysis Intelligence IndexSource 37.8%39.5%GLM-5 leads
AA-GPQA DiamondSource 84.0%82.0%Claude Opus 4.6 leads
AA-HLESource 18.6%27.2%GLM-5 leads
AA-Omniscience IndexSource 3.5%2.0%Claude Opus 4.6 leads
AA-Omniscience AccuracySource 45.2%26.9%Claude Opus 4.6 leads
AA-Omniscience Hallucination RateSource 76.0%34.0%GLM-5 leads
MathGLM-5 wins
BenchmarkClaude Opus 4.6GLM-5Result
AIME25 (Arcee)Source 99.8%93.3%Claude Opus 4.6 leads
FrontierMath v2 (Tiers 1-3)Source 40.700%16.434%Claude Opus 4.6 leads
FrontierMath v2 (Tier 4)Source 22.900%2.100%Claude Opus 4.6 leads
AIME26Source —95.8%Not comparable
HMMT Feb 2025Source —97.5%Not comparable
HMMT Nov 2025Source —96.9%Not comparable
HMMT Feb 2026Source —86.4%Not comparable
MMAnswerBenchSource —82.5%Not comparable
Multilingual
BenchmarkClaude Opus 4.6GLM-5Result
MMLU-ProXSource —83.1%Not comparable
NOVA-63Source —55.1%Not comparable
Multimodal
BenchmarkClaude Opus 4.6GLM-5Result
MMMU-ProSource 77.3%—Not comparable
ERQASource 51.6%—Not comparable
ScreenSpot ProSource 83.1%—Not comparable
MedXpertQA (MM)Source 64.8%—Not comparable
AA-MMMU-ProSource 72.5%—Not comparable
Design Arena WebsiteSource 13281280Claude Opus 4.6 leads
Inst. Following
BenchmarkClaude Opus 4.6GLM-5Result
AA-IFBenchSource 44.6%72.3%GLM-5 leads
IFEvalSource —92.6%Not comparable
Frequently Asked Questions (5)

Which is better, Claude Opus 4.6 or GLM-5?

Claude Opus 4.6 is ahead on BenchLM's BenchAlign leaderboard, 68.59 to 66.06. The biggest single separator in this matchup is SuperGPQA, where the scores are 95% and 66.8%.

Which is better for knowledge tasks, Claude Opus 4.6 or GLM-5?

Claude Opus 4.6 has the edge for knowledge tasks in this comparison, averaging 69.1 versus 66.4. Inside this category, AA-Omniscience Hallucination Rate is the benchmark that creates the most daylight between them.

Which is better for coding, Claude Opus 4.6 or GLM-5?

Claude Opus 4.6 has the edge for coding in this comparison, averaging 68.1 versus 66.3. Inside this category, React Native Evals is the benchmark that creates the most daylight between them.

Which is better for math, Claude Opus 4.6 or GLM-5?

GLM-5 has the edge for math in this comparison, averaging 56.3 versus 36.3. 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 4.6 or GLM-5?

Claude Opus 4.6 has the edge for agentic tasks in this comparison, averaging 73 versus 56.2. Inside this category, CyberGym is the benchmark that creates the most daylight between them.

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