Model comparison
Celeris-1 vs K-Exaone
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: Celeris-1 unranked (Not scored); K-Exaone #126 (Estimated). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. Celeris-1 and K-Exaone share 0 comparable benchmark results. 0 of 8 categories are comparable. 1 result is unique to Celeris-1; 11 to K-Exaone.
Updated July 24, 2026- Shared results
- 0
- Celeris-1 only
- 1
- K-Exaone only
- 11
- Comparable categories
- 0 / 8
Benchmark data for Celeris-1 and K-Exaone 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.
K-Exaone has the larger context window at 256K, compared with 8K for Celeris-1.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | Celeris-1 | K-Exaone | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | Celeris-1$2 input / $6 output | K-ExaoneNot available | A complete price comparison is not available. |
| Generation speedtokens per second | Celeris-1Not available | K-ExaoneNot available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | Celeris-1Not available | K-ExaoneNot available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | Celeris-18K | K-Exaone256K | K-Exaone lists the larger context window. |
Benchmark Deep Dive
Agentic1 benchmarks
| Benchmark | Celeris-1 | K-Exaone | Result |
|---|---|---|---|
| τ²-bench resultsSource | — | 74.3% | Not comparable |
Coding1 benchmarks
| Benchmark | Celeris-1 | K-Exaone | Result |
|---|---|---|---|
| AA-SciCodeSource | — | 35.6% | Not comparable |
Reasoning2 benchmarks
Knowledge7 benchmarks
| Benchmark | Celeris-1 | K-Exaone | Result |
|---|---|---|---|
| MMLU-ProSource | 75.9% | — | Not comparable |
| 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 | Celeris-1 | K-Exaone | Result |
|---|---|---|---|
| AA-IFBenchSource | — | 64.7% | Not comparable |
Frequently Asked Questions (3)
Can I compare Celeris-1 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 Celeris-1 and K-Exaone today?
Celeris-1: $2.00 input / $6.00 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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