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Model comparison

GLM-4.6 vs K-Exaone

Data verified

Head-to-head evidence from 11 shared benchmark results across 5 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.

55.12/100
Margin
6.7pts
← winning
LG AI Research
48.45/100
0 category wins0 category wins

Public leaderboard positions: GLM-4.6 #85 (Supported); K-Exaone #126 (Estimated). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.

Evidence parity. GLM-4.6 and K-Exaone share 11 comparable benchmark results. 0 of 8 categories are comparable. 3 results are unique to GLM-4.6; 0 to K-Exaone.

Updated July 23, 2026
Shared results
11
GLM-4.6 only
3
K-Exaone only
0
Comparable categories
0 / 8

Benchmark data for GLM-4.6 and K-Exaone is coming soon on BenchLM.

Confidence note. This is a partial-evidence comparison with 11 shared benchmark results across 5 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.

K-Exaone has the larger context window at 256K, compared with 200K for GLM-4.6.

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 GLM-4.6 and K-Exaone
CategoryGLM-4.6ΔK-Exaone
MathGLM-4.63.4MarginNo overlapK-ExaoneNot measured

Operational comparison

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

MetricGLM-4.6K-ExaoneComparison
Input / output priceUSD per 1M tokensGLM-4.6Not availableK-ExaoneNot availableA complete price comparison is not available.
Generation speedtokens per secondGLM-4.6Not availableK-ExaoneNot availableA complete speed comparison is not available.
First-answer latencyseconds to first tokenGLM-4.6Not availableK-ExaoneNot availableA complete latency comparison is not available.
Context windowmaximum listed tokensGLM-4.6200KK-Exaone256KK-Exaone lists the larger context window.

Benchmark Deep Dive

Agentic
BenchmarkGLM-4.6K-ExaoneResult
τ²-bench resultsSource 76.9%74.3%GLM-4.6 leads
Coding
BenchmarkGLM-4.6K-ExaoneResult
Vibe Code BenchSource 3.09%Not comparable
AA-SciCodeSource 33.1%35.6%K-Exaone leads
Reasoning
BenchmarkGLM-4.6K-ExaoneResult
AA-LCRSource 26.3%55.7%K-Exaone leads
CritPtSource 0.0%1.1%K-Exaone leads
Knowledge
BenchmarkGLM-4.6K-ExaoneResult
Artificial Analysis Intelligence IndexSource 23.0%24.7%K-Exaone leads
AA-GPQA DiamondSource 63.2%78.3%K-Exaone leads
AA-HLESource 5.2%13.1%K-Exaone leads
AA-Omniscience IndexSource -31.6%-57.9%GLM-4.6 leads
AA-Omniscience AccuracySource 20.8%16.5%GLM-4.6 leads
AA-Omniscience Hallucination RateSource 66.1%89.1%GLM-4.6 leads
Math
BenchmarkGLM-4.6K-ExaoneResult
FrontierMath v2 (Tiers 1-3)Source 3.819%Not comparable
FrontierMath v2 (Tier 4)Source 2.128%Not comparable
Inst. Following
BenchmarkGLM-4.6K-ExaoneResult
AA-IFBenchSource 36.7%64.7%K-Exaone leads
Frequently Asked Questions (2)

Can I compare GLM-4.6 and K-Exaone 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.

Related Comparisons

Last updated: July 23, 2026

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