Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
Gemini 2.5 Pro is clearly ahead on the aggregate, 55 to 49. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Gemini 2.5 Pro's sharpest advantage is in coding, where it averages 63.8 against 49.4. The single biggest benchmark swing on the page is SWE-bench Verified, 63.8% to 49.4%.
K-Exaone is the reasoning model in the pair, while Gemini 2.5 Pro 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. Gemini 2.5 Pro gives you the larger context window at 1M, compared with 256K for K-Exaone.
Pick Gemini 2.5 Pro if you want the stronger benchmark profile. K-Exaone only becomes the better choice if you want the stronger reasoning-first profile.
Benchmark data for this category is coming soon.
Gemini 2.5 Pro
63.8
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.
Benchmark data for this category is coming soon.
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.
Gemini 2.5 Pro is ahead overall, 55 to 49. The biggest single separator in this matchup is SWE-bench Verified, where the scores are 63.8% and 49.4%.
Gemini 2.5 Pro has the edge for coding in this comparison, averaging 63.8 versus 49.4. Inside this category, SWE-bench Verified is the benchmark that creates the most daylight between them.
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