Model comparison
Gemini 1.5 Pro vs K-Exaone
Head-to-head evidence from 4 shared benchmark results across 2 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: Gemini 1.5 Pro #185 (Supported); K-Exaone #126 (Estimated). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. Gemini 1.5 Pro and K-Exaone share 4 comparable benchmark results. 0 of 8 categories are comparable. 2 results are unique to Gemini 1.5 Pro; 7 to K-Exaone.
Updated July 18, 2026- Shared results
- 4
- Gemini 1.5 Pro only
- 2
- K-Exaone only
- 7
- Comparable categories
- 0 / 8
Benchmark data for Gemini 1.5 Pro and K-Exaone is coming soon on BenchLM.
Confidence note. This is a partial-evidence comparison with 4 shared benchmark results across 2 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.
Gemini 1.5 Pro has the larger context window at 2M, 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.
| Metric | Gemini 1.5 Pro | K-Exaone | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | Gemini 1.5 Pro$1.25 input / $5 output | K-ExaoneNot available | A complete price comparison is not available. |
| Generation speedtokens per second | Gemini 1.5 ProNot available | K-ExaoneNot available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | Gemini 1.5 ProNot available | K-ExaoneNot available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | Gemini 1.5 Pro2M | K-Exaone256K | Gemini 1.5 Pro lists the larger context window. |
Benchmark Deep Dive
Agentic1 benchmarks
| Benchmark | Gemini 1.5 Pro | K-Exaone | Result |
|---|---|---|---|
| τ²-bench resultsSource | — | 74.3% | Not comparable |
Coding2 benchmarks
Reasoning2 benchmarks
Knowledge6 benchmarks
| Benchmark | Gemini 1.5 Pro | K-Exaone | Result |
|---|---|---|---|
| Artificial Analysis Intelligence IndexSource | 10.0% | 24.7% | K-Exaone leads |
| AA-GPQA DiamondSource | 58.9% | 78.3% | K-Exaone leads |
| AA-HLESource | 4.9% | 13.1% | K-Exaone leads |
| AA-Omniscience IndexSource | — | -57.9% | Not comparable |
| AA-Omniscience AccuracySource | — | 16.5% | Not comparable |
| AA-Omniscience Hallucination RateSource | — | 89.1% | Not comparable |
Multimodal1 benchmarks
| Benchmark | Gemini 1.5 Pro | K-Exaone | Result |
|---|---|---|---|
| AA-MMMU-ProSource | 55.0% | — | Not comparable |
Inst. Following1 benchmarks
| Benchmark | Gemini 1.5 Pro | K-Exaone | Result |
|---|---|---|---|
| AA-IFBenchSource | — | 64.7% | Not comparable |
Frequently Asked Questions (3)
Can I compare Gemini 1.5 Pro 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.
What data is available for Gemini 1.5 Pro and K-Exaone today?
Gemini 1.5 Pro: $1.25 input / $5.00 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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