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Model comparison

GLM-4.7 vs GLM-4.7-Flash

Data verified

Head-to-head evidence from 0 shared benchmark results across 0 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.

No sourced benchmark result is currently shared by both models. This page therefore compares only the available metadata, pricing, and runtime rows; it does not name a quality winner.
61.16/100
No comparison
N/A
0 category wins0 category wins

Public leaderboard positions: GLM-4.7 #42 (Supported); GLM-4.7-Flash #106 (Supported). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.

Evidence parity. GLM-4.7 and GLM-4.7-Flash share 0 comparable benchmark results. 0 of 8 categories are comparable. 30 results are unique to GLM-4.7; 0 to GLM-4.7-Flash.

Updated July 22, 2026
Shared results
0
GLM-4.7 only
30
GLM-4.7-Flash only
0
Comparable categories
0 / 8

Benchmark data for GLM-4.7 and GLM-4.7-Flash is coming soon on BenchLM.

Confidence note. This is a partial-evidence comparison with 0 shared benchmark results across 0 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 does not have sourced benchmark coverage for GLM-4.7-Flash yet. This comparison is currently limited to metadata such as context window, reasoning mode, and pricing where available.

Operational comparison

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

MetricGLM-4.7GLM-4.7-FlashComparison
Input / output priceUSD per 1M tokensGLM-4.7$0 input / $0 outputGLM-4.7-Flash$0 input / $0 outputListed prices are equal.
Generation speedtokens per secondGLM-4.782 tok/sGLM-4.7-Flash95 tok/sGLM-4.7-Flash has the higher measured throughput.
First-answer latencyseconds to first tokenGLM-4.71.10 sGLM-4.7-Flash0.91 sGLM-4.7-Flash reaches the first token sooner.
Context windowmaximum listed tokensGLM-4.7200KGLM-4.7-Flash200KListed context windows are equal.

Benchmark Deep Dive

Agentic
BenchmarkGLM-4.7GLM-4.7-FlashResult
Terminal-Bench 2.0Source 41%—Not comparable
BrowseCompSource 52%—Not comparable
VITA-BenchSource 15.5%—Not comparable
AA Agentic IndexSource 25.4%—Not comparable
τ²-bench resultsSource 95.9%—Not comparable
Gert LabsSource 39.95%—Not comparable
GDPval-AASource 33.3%—Not comparable
GDPval-AASource 1165—Not comparable
Coding
BenchmarkGLM-4.7GLM-4.7-FlashResult
SWE-bench VerifiedSource 73.8%—Not comparable
LiveCodeBenchSource 84.9%—Not comparable
SWE-RebenchSource 58.7%—Not comparable
AA Coding IndexSource 45.3%—Not comparable
AA-SciCodeSource 45.1%—Not comparable
AA LiveCodeBenchSource 89.4%—Not comparable
Reasoning
BenchmarkGLM-4.7GLM-4.7-FlashResult
AA-LCRSource 64.0%—Not comparable
CritPtSource 1.7%—Not comparable
Knowledge
BenchmarkGLM-4.7GLM-4.7-FlashResult
GPQASource 85.7%—Not comparable
MMLU-ProSource 84.3%—Not comparable
HLESource 24.8%—Not comparable
Artificial Analysis Intelligence IndexSource 33.7%—Not comparable
AA-GPQA DiamondSource 85.9%—Not comparable
AA-HLESource 25.1%—Not comparable
AA-Omniscience IndexSource -34.6%—Not comparable
AA-Omniscience AccuracySource 29.3%—Not comparable
AA-Omniscience Hallucination RateSource 90.3%—Not comparable
Math
BenchmarkGLM-4.7GLM-4.7-FlashResult
AIME 2025Source 95.7%—Not comparable
FrontierMath v2 (Tiers 1-3)Source 2.439%—Not comparable
FrontierMath v2 (Tier 4)Source 0.000%—Not comparable
Multimodal
BenchmarkGLM-4.7GLM-4.7-FlashResult
Design Arena WebsiteSource 1255—Not comparable
Inst. Following
BenchmarkGLM-4.7GLM-4.7-FlashResult
AA-IFBenchSource 67.9%—Not comparable
Frequently Asked Questions (3)

Can I compare GLM-4.7 and GLM-4.7-Flash 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 GLM-4.7 and GLM-4.7-Flash today?

GLM-4.7: $0.00 input / $0.00 output per 1M tokens GLM-4.7-Flash: $0.00 input / $0.00 output per 1M tokens Both model pages still include creator, context window, reasoning mode, and other metadata while benchmark coverage fills in.

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