Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
K-Exaone finishes one point ahead overall, 49 to 48. That is enough to call, but not enough to treat as a blowout. This matchup comes down to a few meaningful edges rather than one model dominating the board.
K-Exaone's sharpest advantage is in coding, where it averages 49.4 against 10. The single biggest benchmark swing on the page is SWE-bench Verified, 10% to 49.4%.
K-Exaone is the reasoning model in the pair, while Claude 3 Opus 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. K-Exaone gives you the larger context window at 256K, compared with 200K for Claude 3 Opus.
Pick K-Exaone if you want the stronger benchmark profile. Claude 3 Opus only becomes the better choice if you would rather avoid the extra latency and token burn of a reasoning model.
Benchmark data for this category is coming soon.
Claude 3 Opus
10
K-Exaone
49.4
Benchmark data for this category is coming soon.
Comparable scores for this category are coming soon. One or both models do not have sourced results here yet.
Comparable scores for this category are coming soon. One or both models do not have sourced results here yet.
Comparable scores for this category are coming soon. One or both models do not have sourced results here yet.
Benchmark data for this category is coming soon.
Comparable scores for this category are coming soon. One or both models do not have sourced results here yet.
K-Exaone is ahead overall, 49 to 48. The biggest single separator in this matchup is SWE-bench Verified, where the scores are 10% and 49.4%.
K-Exaone has the edge for coding in this comparison, averaging 49.4 versus 10. Inside this category, SWE-bench Verified is the benchmark that creates the most daylight between them.
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