Model comparison
K-Exaone vs Trinity-Large-Thinking
Head-to-head evidence from 12 shared benchmark results across 5 categories. Overall scores shown here use BenchLM's provisional ranking lane.
Evidence parity. K-Exaone and Trinity-Large-Thinking share 12 comparable benchmark results. 0 of 8 categories are comparable. 0 results are unique to K-Exaone; 8 to Trinity-Large-Thinking.
Updated July 14, 2026- Shared results
- 12
- K-Exaone only
- 0
- Trinity-Large-Thinking only
- 8
- Comparable categories
- 0 / 8
Benchmark data for K-Exaone and Trinity-Large-Thinking is coming soon on BenchLM.
Confidence note. This is a partial-evidence comparison with 12 shared benchmark results across 5 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.
Trinity-Large-Thinking has the larger context window at 512K, 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 | K-Exaone | Trinity-Large-Thinking | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | K-ExaoneNot available | Trinity-Large-Thinking$0.25 input / $0.9 output | A complete price comparison is not available. |
| Generation speedtokens per second | K-ExaoneNot available | Trinity-Large-ThinkingNot available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | K-ExaoneNot available | Trinity-Large-ThinkingNot available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | K-Exaone256K | Trinity-Large-Thinking512K | Trinity-Large-Thinking lists the larger context window. |
Benchmark Deep Dive
Agentic4 benchmarks
Coding3 benchmarks
Reasoning2 benchmarks
Knowledge8 benchmarks
| Benchmark | K-Exaone | Trinity-Large-Thinking | Result |
|---|---|---|---|
| Artificial Analysis Intelligence IndexSource | 24.7% | 24.5% | K-Exaone leads |
| AA-GPQA DiamondSource | 78.3% | 75.2% | K-Exaone leads |
| AA-HLESource | 13.1% | 14.7% | Trinity-Large-Thinking leads |
| AA-Omniscience IndexSource | -57.9% | -44.2% | Trinity-Large-Thinking leads |
| AA-Omniscience AccuracySource | 16.5% | 22.8% | Trinity-Large-Thinking leads |
| AA-Omniscience Hallucination RateSource | 89.1% | 86.6% | Trinity-Large-Thinking leads |
| GPQA-DSource | — | 76.3% | Not comparable |
| MMLU-Pro (Arcee)Source | — | 83.4% | Not comparable |
Math1 benchmarks
| Benchmark | K-Exaone | Trinity-Large-Thinking | Result |
|---|---|---|---|
| AIME25 (Arcee)Source | — | 96.3% | Not comparable |
Multimodal1 benchmarks
| Benchmark | K-Exaone | Trinity-Large-Thinking | Result |
|---|---|---|---|
| Design Arena WebsiteSource | — | 1169 | Not comparable |
Inst. Following1 benchmarks
| Benchmark | K-Exaone | Trinity-Large-Thinking | Result |
|---|---|---|---|
| AA-IFBenchSource | 64.7% | 56.3% | K-Exaone leads |
Frequently Asked Questions (3)
Can I compare K-Exaone and Trinity-Large-Thinking 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 Trinity-Large-Thinking today?
Trinity-Large-Thinking: $0.25 input / $0.90 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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