Model comparison
K-Exaone vs o1-pro
Head-to-head evidence from 1 shared benchmark result across 1 category. Overall scores shown here use BenchLM's provisional ranking lane.
Evidence parity. K-Exaone and o1-pro share 1 comparable benchmark result. 0 of 8 categories are comparable. 11 results are unique to K-Exaone; 1 to o1-pro.
Updated July 14, 2026- Shared results
- 1
- K-Exaone only
- 11
- o1-pro only
- 1
- Comparable categories
- 0 / 8
Benchmark data for K-Exaone and o1-pro is coming soon on BenchLM.
Confidence note. This is a partial-evidence comparison with 1 shared benchmark result across 1 evidence category; 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 o1-pro.
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 | K-Exaone | Δ | o1-pro |
|---|---|---|---|
| Knowledge | K-ExaoneNot measured | MarginNo overlap | o1-pro79.0 |
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | K-Exaone | o1-pro | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | K-ExaoneNot available | o1-pro$150 input / $600 output | A complete price comparison is not available. |
| Generation speedtokens per second | K-ExaoneNot available | o1-proNot available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | K-ExaoneNot available | o1-proNot available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | K-Exaone256K | o1-pro200K | K-Exaone lists the larger context window. |
Benchmark Deep Dive
Agentic1 benchmarks
| Benchmark | K-Exaone | o1-pro | Result |
|---|---|---|---|
| Tau2-TelecomSource | 74.3% | — | Not comparable |
Coding2 benchmarks
Reasoning2 benchmarks
Knowledge7 benchmarks
| Benchmark | K-Exaone | o1-pro | Result |
|---|---|---|---|
| Artificial Analysis Intelligence IndexSource | 24.7% | 18.9% | K-Exaone leads |
| AA-GPQA DiamondSource | 78.3% | — | Not comparable |
| AA-HLESource | 13.1% | — | Not comparable |
| AA-Omniscience IndexSource | -57.9% | — | Not comparable |
| AA-Omniscience AccuracySource | 16.5% | — | Not comparable |
| AA-Omniscience Hallucination RateSource | 89.1% | — | Not comparable |
| GPQASource | — | 79% | Not comparable |
Inst. Following1 benchmarks
| Benchmark | K-Exaone | o1-pro | Result |
|---|---|---|---|
| AA-IFBenchSource | 64.7% | — | Not comparable |
Frequently Asked Questions (3)
Can I compare K-Exaone and o1-pro 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 K-Exaone and o1-pro today?
o1-pro: $150.00 input / $600.00 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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