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BenchLM

Model comparison

Claude Opus 4.8 vs GLM-5

Data verified

Head-to-head evidence from 25 shared benchmark results across 7 categories. Overall scores shown here use BenchLM's provisional ranking lane.

85/100
Margin
22.0pts
← winning
GLM-5
Z.AI
63/100
2 category wins2 category wins

Verified leaderboard positions: Claude Opus 4.8 #3; GLM-5 #18

Evidence parity. Claude Opus 4.8 and GLM-5 share 25 comparable benchmark results. 4 of 8 categories are comparable. 28 results are unique to Claude Opus 4.8; 25 to GLM-5.

Updated July 12, 2026
Shared results
25
Claude Opus 4.8 only
28
GLM-5 only
25
Comparable categories
4 / 8

Pick Claude Opus 4.8 if you want the stronger benchmark profile. GLM-5 only becomes the better choice if knowledge is the priority or you want the cheaper token bill.

Confidence note. This is a partial-evidence comparison with 25 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 4.8 is clearly ahead on the provisional aggregate, 85 to 63. 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 agentic, where it averages 80.3 against 56.2. The single biggest benchmark swing on the page is FrontierMath v2 (Tiers 1-3), 47.241% to 16.434%. GLM-5 does hit back in knowledge, 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 $1.00 input / $3.20 output per 1M tokens for GLM-5. That is roughly 7.8x on output cost alone. Claude Opus 4.8 is the reasoning model in the pair, while GLM-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. Claude Opus 4.8 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 4.8 and GLM-5
CategoryClaude Opus 4.8ΔGLM-5
AgenticClaude Opus 4.880.3Margin← 24.1GLM-556.2
CodingClaude Opus 4.876.4Margin← 13.1GLM-563.3
KnowledgeClaude Opus 4.862.7Margin→ 3.9GLM-566.6
MathClaude Opus 4.853.9Margin→ 2.4GLM-556.3
ReasoningClaude Opus 4.8Not measuredMarginNo overlapGLM-560.8
MultilingualClaude Opus 4.8Not measuredMarginNo overlapGLM-583.1
MultimodalClaude Opus 4.877.0MarginNo overlapGLM-5Not measured
Inst. FollowingClaude Opus 4.8Not measuredMarginNo overlapGLM-592.6

Decisive benchmark drivers

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

More
A · Claude Opus 4.8B · GLM-5

  1. FrontierMath v2 (Tiers 1-3)

    Math
    Source ↗
    A 47.241%B 16.434%
    Winner: Claude Opus 4.8Δ 30.8
    FrontierMath v2 (Tiers 1-3): Claude Opus 4.8 scored 47.241%; GLM-5 scored 16.434%. Claude Opus 4.8 wins this benchmark.

  2. FrontierMath v2 (Tier 4)

    Math
    Source ↗
    A 31.250%B 2.100%
    Winner: Claude Opus 4.8Δ 29.2
    FrontierMath v2 (Tier 4): Claude Opus 4.8 scored 31.250%; GLM-5 scored 2.100%. Claude Opus 4.8 wins this benchmark.

  3. Terminal-Bench 2.0

    Agentic
    Source ↗
    A 74.6%B 56.2%
    Winner: Claude Opus 4.8Δ 18.4
    Terminal-Bench 2.0: Claude Opus 4.8 scored 74.6%; GLM-5 scored 56.2%. Claude Opus 4.8 wins this benchmark.

  4. SWE-bench Pro

    Coding
    Source ↗
    A 69.2%B 55.1%
    Winner: Claude Opus 4.8Δ 14.1
    SWE-bench Pro: Claude Opus 4.8 scored 69.2%; GLM-5 scored 55.1%. Claude Opus 4.8 wins this benchmark.

  5. SWE-bench Verified

    Coding
    Source ↗
    A 88.6%B 77.8%
    Winner: Claude Opus 4.8Δ 10.8
    SWE-bench Verified: Claude Opus 4.8 scored 88.6%; GLM-5 scored 77.8%. 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-5Comparison
Input / output priceUSD per 1M tokensClaude Opus 4.8$5 input / $25 outputGLM-5$1 input / $3.2 outputGLM-5 has the lower combined listed price.
Generation speedtokens per secondClaude Opus 4.8Not availableGLM-574 tok/sA complete speed comparison is not available.
First-answer latencyseconds to first tokenClaude Opus 4.8Not availableGLM-51.64 sA complete latency comparison is not available.
Context windowmaximum listed tokensClaude Opus 4.81MGLM-5200KClaude Opus 4.8 lists the larger context window.

Benchmark Deep Dive

AgenticClaude Opus 4.8 wins
BenchmarkClaude Opus 4.8GLM-5Result
Terminal-Bench 2.0Source 74.6%56.2%Claude Opus 4.8 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 1600—Not comparable
MCP AtlasSource 82.2%31.1%Claude Opus 4.8 leads
ToolathlonSource 59.9%38%Claude Opus 4.8 leads
Gert LabsSource 72.97%50.99%Claude Opus 4.8 leads
AA Agentic IndexSource 47.2%—Not comparable
Tau2-TelecomSource 94.4%98.2%GLM-5 leads
GDPval-AASource 55.0%—Not comparable
ResearchClawBenchSource 21.1%—Not comparable
OSWorld 2.0Source 20.6%—Not comparable
AA BriefcaseSource 1354—Not comparable
AA AutomationBenchSource 48.5%—Not comparable
AA EnterpriseOps-GymSource 44.0%—Not comparable
AA Harvey LABSource 7.5%—Not comparable
AA Tau3 BankingSource 27.6%—Not comparable
Claw-EvalSource —57.7%Not comparable
QwenClawBenchSource —54.1%Not comparable
TAU3-BenchSource —65.6%Not comparable
DeepPlanningSource —14.6%Not comparable
MCP-TasksSource —60.8%Not comparable
WideResearchSource —69.8%Not comparable
CyberGymSource —43.2%Not comparable
APEX-Agents-AASource —14.5%Not comparable
CodingClaude Opus 4.8 wins
BenchmarkClaude Opus 4.8GLM-5Result
SWE-bench VerifiedSource 88.6%77.8%Claude Opus 4.8 leads
SWE-bench ProSource 69.2%55.1%Claude Opus 4.8 leads
SWE MultilingualSource 84.4%73.3%Claude Opus 4.8 leads
SWE MultimodalSource 38.4%—Not comparable
Terminal-Bench 2.0Source 74.6%—Not comparable
cursorBench31Source 58.4%—Not comparable
cursorBench32Source 62.3%—Not comparable
AA Coding IndexSource 74.3%—Not comparable
Terminal-Bench HardSource 58.3%43.2%Claude Opus 4.8 leads
AA-SciCodeSource 53.5%46.2%Claude Opus 4.8 leads
FrontierCodeSource 46.5%—Not comparable
AA Terminal-Bench 2.1Source 84.6%—Not comparable
SWE-bench Verified*Source —72.8%Not comparable
SWE-RebenchSource —62.8%Not comparable
React Native EvalsSource —74.8%Not comparable
Reasoning
BenchmarkClaude Opus 4.8GLM-5Result
AA-LCRSource 67.7%63.3%Claude Opus 4.8 leads
CritPtSource 20.9%2.0%Claude Opus 4.8 leads
LongBench v2Source —60.8%Not comparable
AI-NeedleSource —63.3%Not comparable
KnowledgeGLM-5 wins
BenchmarkClaude Opus 4.8GLM-5Result
GPQASource 93.6%86%Claude Opus 4.8 leads
GPQA-DSource 93.6%86.0%Claude Opus 4.8 leads
HLESource 57.9%50.4%Claude Opus 4.8 leads
HLE w/o toolsSource 49.8%—Not comparable
Artificial Analysis Intelligence IndexSource 55.7%39.5%Claude Opus 4.8 leads
AA-GPQA DiamondSource 92.0%82.0%Claude Opus 4.8 leads
AA-HLESource 45.7%27.2%Claude Opus 4.8 leads
AA-Omniscience IndexSource 27.4%2.0%Claude Opus 4.8 leads
AA-Omniscience AccuracySource 46.6%26.9%Claude Opus 4.8 leads
AA-Omniscience Hallucination RateSource 35.9%34.0%GLM-5 leads
SuperGPQASource —66.8%Not comparable
MMLU-ProSource —85.7%Not comparable
MMLU-Pro (Arcee)Source —85.8%Not comparable
MathGLM-5 wins
BenchmarkClaude Opus 4.8GLM-5Result
USAMO 2026Source 96.7%—Not comparable
FrontierMath v2 (Tiers 1-3)Source 47.241%16.434%Claude Opus 4.8 leads
FrontierMath v2 (Tier 4)Source 31.250%2.100%Claude Opus 4.8 leads
AIME26Source —95.8%Not comparable
AIME25 (Arcee)Source —93.3%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 4.8GLM-5Result
INCLUDESource 87.6%—Not comparable
MMLU-ProXSource —83.1%Not comparable
NOVA-63Source —55.1%Not comparable
Multimodal
BenchmarkClaude Opus 4.8GLM-5Result
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 12811291GLM-5 leads
Inst. Following
BenchmarkClaude Opus 4.8GLM-5Result
AA-IFBenchSource 62.2%72.3%GLM-5 leads
IFEvalSource —92.6%Not comparable
Frequently Asked Questions (5)

Which is better, Claude Opus 4.8 or GLM-5?

Claude Opus 4.8 is ahead on BenchLM's provisional leaderboard, 85 to 63. The biggest single separator in this matchup is FrontierMath v2 (Tiers 1-3), where the scores are 47.241% and 16.434%.

Which is better for knowledge tasks, Claude Opus 4.8 or GLM-5?

GLM-5 has the edge for knowledge tasks in this comparison, averaging 66.6 versus 62.7. 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?

Claude Opus 4.8 has the edge for coding in this comparison, averaging 76.4 versus 63.3. Inside this category, Terminal-Bench Hard is the benchmark that creates the most daylight between them.

Which is better for math, Claude Opus 4.8 or GLM-5?

GLM-5 has the edge for math in this comparison, averaging 56.3 versus 53.9. 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 4.8 or GLM-5?

Claude Opus 4.8 has the edge for agentic tasks in this comparison, averaging 80.3 versus 56.2. Inside this category, MCP Atlas is the benchmark that creates the most daylight between them.

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