Skip to main content

Model comparison

Claude Opus 4.7 (Adaptive) vs GLM-5-Turbo

Data verified

Head-to-head evidence from 12 shared benchmark results across 6 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.

66.27/100
Margin
0.6pts
winning →
66.89/100
0 category wins0 category wins

Public leaderboard positions: Claude Opus 4.7 (Adaptive) #27 (Estimated); GLM-5-Turbo #24 (Supported). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.

Evidence parity. Claude Opus 4.7 (Adaptive) and GLM-5-Turbo share 12 comparable benchmark results. 0 of 8 categories are comparable. 26 results are unique to Claude Opus 4.7 (Adaptive); 1 to GLM-5-Turbo.

Updated July 23, 2026
Shared results
12
Claude Opus 4.7 (Adaptive) only
26
GLM-5-Turbo only
1
Comparable categories
0 / 8

Benchmark data for Claude Opus 4.7 (Adaptive) and GLM-5-Turbo is coming soon on BenchLM.

Confidence note. This is a partial-evidence comparison with 12 shared benchmark results across 6 evidence categories; 0 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.

Why this result

BenchLM has partial data for these models, but not enough overlapping benchmark coverage to produce a fair score-level comparison yet.

Claude Opus 4.7 (Adaptive) is priced at $5.00 input / $25.00 output per 1M tokens, versus $1.20 input / $4.00 output per 1M tokens for GLM-5-Turbo. Claude Opus 4.7 (Adaptive) has the larger context window at 1M, compared with 200K for GLM-5-Turbo.

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 4.7 (Adaptive) and GLM-5-Turbo
CategoryClaude Opus 4.7 (Adaptive)ΔGLM-5-Turbo
AgenticClaude Opus 4.7 (Adaptive)75.1MarginNo overlapGLM-5-TurboNot measured
CodingClaude Opus 4.7 (Adaptive)78.6MarginNo overlapGLM-5-TurboNot measured
ReasoningClaude Opus 4.7 (Adaptive)75.8MarginNo overlapGLM-5-TurboNot measured
KnowledgeClaude Opus 4.7 (Adaptive)60.0MarginNo overlapGLM-5-TurboNot measured
MultimodalClaude Opus 4.7 (Adaptive)65.1MarginNo overlapGLM-5-TurboNot measured

Operational comparison

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

MetricClaude Opus 4.7 (Adaptive)GLM-5-TurboComparison
Input / output priceUSD per 1M tokensClaude Opus 4.7 (Adaptive)$5 input / $25 outputGLM-5-Turbo$1.2 input / $4 outputGLM-5-Turbo has the lower combined listed price.
Generation speedtokens per secondClaude Opus 4.7 (Adaptive)Not availableGLM-5-TurboNot availableA complete speed comparison is not available.
First-answer latencyseconds to first tokenClaude Opus 4.7 (Adaptive)Not availableGLM-5-TurboNot availableA complete latency comparison is not available.
Context windowmaximum listed tokensClaude Opus 4.7 (Adaptive)1MGLM-5-Turbo200KClaude Opus 4.7 (Adaptive) lists the larger context window.

Benchmark Deep Dive

Agentic
BenchmarkClaude Opus 4.7 (Adaptive)GLM-5-TurboResult
Terminal-Bench 2.0Source 69.4%Not comparable
BrowseCompSource 79.3%Not comparable
MCP AtlasSource 77.3%Not comparable
OSWorld-VerifiedSource 78%Not comparable
CyberGymSource 73.1%Not comparable
AA Agentic IndexSource 44.4%Not comparable
τ²-bench resultsSource 88.6%98.5%GLM-5-Turbo leads
GDPval-AASource 49.8%Not comparable
GDPval-AASource 1495Not comparable
OSWorld 2.0Source 18.2%Not comparable
JobBenchSource 45.9%Not comparable
AA ITBenchSource 46.7%Not comparable
Claw-EvalSource 55.8%Not comparable
Coding
BenchmarkClaude Opus 4.7 (Adaptive)GLM-5-TurboResult
SWE-bench VerifiedSource 87.6%Not comparable
SWE-bench ProSource 64.3%Not comparable
Terminal-Bench 2.0Source 69.4%Not comparable
AA Coding IndexSource 73.6%Not comparable
AA-SciCodeSource 54.5%43.6%Claude Opus 4.7 (Adaptive) leads
Reasoning
BenchmarkClaude Opus 4.7 (Adaptive)GLM-5-TurboResult
MRCR v2 128K-256KSource 59.2%Not comparable
ARC-AGI-2Source 75.8%Not comparable
AA-LCRSource 70.3%60.7%Claude Opus 4.7 (Adaptive) leads
CritPtSource 12.0%0.3%Claude Opus 4.7 (Adaptive) leads
Knowledge
BenchmarkClaude Opus 4.7 (Adaptive)GLM-5-TurboResult
GPQASource 94.2%Not comparable
GPQA-DSource 94.2%Not comparable
HLESource 54.7%Not comparable
HLE w/o toolsSource 46.9%Not comparable
Artificial Analysis Intelligence IndexSource 53.5%38.1%Claude Opus 4.7 (Adaptive) leads
AA-GPQA DiamondSource 91.4%84.7%Claude Opus 4.7 (Adaptive) leads
AA-HLESource 39.6%25.4%Claude Opus 4.7 (Adaptive) leads
AA-Omniscience IndexSource 26.2%-15.1%Claude Opus 4.7 (Adaptive) leads
AA-Omniscience AccuracySource 45.8%29.0%Claude Opus 4.7 (Adaptive) leads
AA-Omniscience Hallucination RateSource 36.2%62.2%Claude Opus 4.7 (Adaptive) leads
Math
BenchmarkClaude Opus 4.7 (Adaptive)GLM-5-TurboResult
FrontierMath (legacy)Source 43.8%Not comparable
Multimodal
BenchmarkClaude Opus 4.7 (Adaptive)GLM-5-TurboResult
OfficeQA ProSource 43.6%Not comparable
CharXivSource 91%Not comparable
CharXiv w/o toolsSource 82.1%Not comparable
AA-MMMU-ProSource 78.8%Not comparable
Design Arena WebsiteSource 13251301Claude Opus 4.7 (Adaptive) leads
Inst. Following
BenchmarkClaude Opus 4.7 (Adaptive)GLM-5-TurboResult
AA-IFBenchSource 58.6%73.2%GLM-5-Turbo leads
Frequently Asked Questions (3)

Can I compare Claude Opus 4.7 (Adaptive) and GLM-5-Turbo on BenchLM yet?

Not fully yet. BenchLM is tracking both models, but the sourced benchmark breakdown for this comparison is still coming soon.

Why does this comparison show “coming soon”?

BenchLM only shows category winners and benchmark-level calls when we have sourced results that can be compared fairly. For these models, the public benchmark coverage is not complete enough yet.

What data is available for Claude Opus 4.7 (Adaptive) and GLM-5-Turbo today?

Claude Opus 4.7 (Adaptive): $5.00 input / $25.00 output per 1M tokens GLM-5-Turbo: $1.20 input / $4.00 output per 1M tokens Both model pages still include creator, context window, reasoning mode, and other metadata while benchmark coverage fills in.

Related Comparisons

Last updated: July 23, 2026

Choose a model with this week’s evidence

Join 2,000+ readers for ranking moves, pricing changes, and the claims that still need proof.

One email each week. Unsubscribe anytime.