Model comparison
K-Exaone vs SWE-1.7
Head-to-head evidence from 0 shared benchmark results across 0 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: K-Exaone #126 (Estimated); SWE-1.7 unranked (Not scored). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. K-Exaone and SWE-1.7 share 0 comparable benchmark results. 0 of 8 categories are comparable. 11 results are unique to K-Exaone; 4 to SWE-1.7.
Updated July 18, 2026- Shared results
- 0
- K-Exaone only
- 11
- SWE-1.7 only
- 4
- Comparable categories
- 0 / 8
Benchmark data for K-Exaone and SWE-1.7 is coming soon on BenchLM.
Confidence note. This is a partial-evidence comparison with 0 shared benchmark results across 0 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.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | K-Exaone | SWE-1.7 | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | K-ExaoneNot available | SWE-1.7Not available | A complete price comparison is not available. |
| Generation speedtokens per second | K-ExaoneNot available | SWE-1.7Not available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | K-ExaoneNot available | SWE-1.7Not available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | K-Exaone256K | SWE-1.7256K | Listed context windows are equal. |
Benchmark Deep Dive
Agentic2 benchmarks
Coding4 benchmarks
Reasoning2 benchmarks
Knowledge6 benchmarks
| Benchmark | K-Exaone | SWE-1.7 | Result |
|---|---|---|---|
| Artificial Analysis Intelligence IndexSource | 24.7% | — | Not comparable |
| 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 |
Inst. Following1 benchmarks
| Benchmark | K-Exaone | SWE-1.7 | Result |
|---|---|---|---|
| AA-IFBenchSource | 64.7% | — | Not comparable |
Frequently Asked Questions (2)
Can I compare K-Exaone and SWE-1.7 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.
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