Skip to main content

Model comparison

Claude Opus 4.6 (Adaptive) 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.

64.18/100
Margin
15.7pts
← winning
LG AI Research
48.45/100
0 category wins0 category wins

Public leaderboard positions: Claude Opus 4.6 (Adaptive) #35 (Estimated); K-Exaone #126 (Estimated). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.

Evidence parity. Claude Opus 4.6 (Adaptive) and K-Exaone share 11 comparable benchmark results. 0 of 8 categories are comparable. 5 results are unique to Claude Opus 4.6 (Adaptive); 0 to K-Exaone.

Updated July 18, 2026
Shared results
11
Claude Opus 4.6 (Adaptive) only
5
K-Exaone only
0
Comparable categories
0 / 8

Benchmark data for Claude Opus 4.6 (Adaptive) 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.

Claude Opus 4.6 (Adaptive) has the larger context window at 1M, compared with 256K for K-Exaone.

Category breakdown

Exact category averages are shown below. Not measured means BenchLM does not have enough sourced public coverage for that model and category.

Operational comparison

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

MetricClaude Opus 4.6 (Adaptive)K-ExaoneComparison
Input / output priceUSD per 1M tokensClaude Opus 4.6 (Adaptive)Not availableK-ExaoneNot availableA complete price comparison is not available.
Generation speedtokens per secondClaude Opus 4.6 (Adaptive)Not availableK-ExaoneNot availableA complete speed comparison is not available.
First-answer latencyseconds to first tokenClaude Opus 4.6 (Adaptive)Not availableK-ExaoneNot availableA complete latency comparison is not available.
Context windowmaximum listed tokensClaude Opus 4.6 (Adaptive)1MK-Exaone256KClaude Opus 4.6 (Adaptive) lists the larger context window.

Benchmark Deep Dive

Agentic
BenchmarkClaude Opus 4.6 (Adaptive)K-ExaoneResult
APEX-Agents-AASource 33.0%Not comparable
τ²-bench resultsSource 92.1%74.3%Claude Opus 4.6 (Adaptive) leads
Coding
BenchmarkClaude Opus 4.6 (Adaptive)K-ExaoneResult
Vibe Code BenchSource 53.50%Not comparable
AA-SciCodeSource 51.9%35.6%Claude Opus 4.6 (Adaptive) leads
Reasoning
BenchmarkClaude Opus 4.6 (Adaptive)K-ExaoneResult
AA-LCRSource 70.7%55.7%Claude Opus 4.6 (Adaptive) leads
CritPtSource 12.6%1.1%Claude Opus 4.6 (Adaptive) leads
Knowledge
BenchmarkClaude Opus 4.6 (Adaptive)K-ExaoneResult
Artificial Analysis Intelligence IndexSource 43.7%24.7%Claude Opus 4.6 (Adaptive) leads
AA-GPQA DiamondSource 89.6%78.3%Claude Opus 4.6 (Adaptive) leads
AA-HLESource 36.7%13.1%Claude Opus 4.6 (Adaptive) leads
AA-Omniscience IndexSource 13.5%-57.9%Claude Opus 4.6 (Adaptive) leads
AA-Omniscience AccuracySource 46.4%16.5%Claude Opus 4.6 (Adaptive) leads
AA-Omniscience Hallucination RateSource 61.3%89.1%Claude Opus 4.6 (Adaptive) leads
Multilingual
BenchmarkClaude Opus 4.6 (Adaptive)K-ExaoneResult
AA Global-MMLU-LiteSource 92.2%Not comparable
Multimodal
BenchmarkClaude Opus 4.6 (Adaptive)K-ExaoneResult
AA-MMMU-ProSource 75.4%Not comparable
Design Arena WebsiteSource 1328Not comparable
Inst. Following
BenchmarkClaude Opus 4.6 (Adaptive)K-ExaoneResult
AA-IFBenchSource 53.1%64.7%K-Exaone leads
Frequently Asked Questions (2)

Can I compare Claude Opus 4.6 (Adaptive) 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 18, 2026

The AI models change fast. We track them for you.

A weekly brief for engineers and researchers covering new models, ranking shifts, and pricing changes.

Free. No spam. Unsubscribe anytime.