Model comparison
K-Exaone vs Kimi K2.7 Code
Head-to-head evidence from 15 shared benchmark results across 5 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: K-Exaone #143 (Estimated); Kimi K2.7 Code #92 (Estimated). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. K-Exaone and Kimi K2.7 Code share 15 comparable benchmark results. 0 of 8 categories are comparable. 0 results are unique to K-Exaone; 8 to Kimi K2.7 Code.
Updated July 27, 2026- Shared results
- 15
- K-Exaone only
- 0
- Kimi K2.7 Code only
- 8
- Comparable categories
- 0 / 8
Benchmark data for K-Exaone and Kimi K2.7 Code is coming soon on BenchLM.
Confidence note. This is a partial-evidence comparison with 15 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.
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 | Kimi K2.7 Code | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | K-ExaoneNot available | Kimi K2.7 Code$0.95 input / $4 output | A complete price comparison is not available. |
| Generation speedtokens per second | K-ExaoneNot available | Kimi K2.7 CodeNot available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | K-ExaoneNot available | Kimi K2.7 CodeNot available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | K-Exaone256K | Kimi K2.7 Code256K | Listed context windows are equal. |
Benchmark Deep Dive
Agentic7 benchmarks
| Benchmark | K-Exaone | Kimi K2.7 Code | Result |
|---|---|---|---|
| τ²-bench resultsSource | 74.3% | 90.1% | Kimi K2.7 Code leads |
| AA Agentic IndexSource | 8.0% | 29.6% | Kimi K2.7 Code leads |
| GDPval-AASource | 4.9% | 34.3% | Kimi K2.7 Code leads |
| GDPval-AASource | 598 | 1186 | Kimi K2.7 Code leads |
| Kimi Claw 24/7Source | — | 46.9% | Not comparable |
| MCP AtlasSource | — | 76% | Not comparable |
| MCP Mark VerifiedSource | — | 81.1% | Not comparable |
Coding6 benchmarks
| Benchmark | K-Exaone | Kimi K2.7 Code | Result |
|---|---|---|---|
| AA-SciCodeSource | 35.6% | 47.5% | Kimi K2.7 Code leads |
| AA Coding IndexSource | 32.1% | 60.8% | Kimi K2.7 Code leads |
| Kimi Code Bench v2Source | — | 62.0% | Not comparable |
| ProgramBenchSource | — | 53.6% | Not comparable |
| MLS-Bench LiteSource | — | 35.1% | Not comparable |
| cursorBench32Source | — | 49.7% | Not comparable |
Reasoning2 benchmarks
Knowledge6 benchmarks
| Benchmark | K-Exaone | Kimi K2.7 Code | Result |
|---|---|---|---|
| Artificial Analysis Intelligence IndexSource | 22.1% | 42.0% | Kimi K2.7 Code leads |
| AA-GPQA DiamondSource | 78.3% | 89.6% | Kimi K2.7 Code leads |
| AA-HLESource | 13.1% | 32.8% | Kimi K2.7 Code leads |
| AA-Omniscience IndexSource | -57.9% | -10.7% | Kimi K2.7 Code leads |
| AA-Omniscience AccuracySource | 16.5% | 38.6% | Kimi K2.7 Code leads |
| AA-Omniscience Hallucination RateSource | 89.1% | 80.3% | Kimi K2.7 Code leads |
Multimodal1 benchmarks
| Benchmark | K-Exaone | Kimi K2.7 Code | Result |
|---|---|---|---|
| Design Arena WebsiteSource | — | 1300 | Not comparable |
Inst. Following1 benchmarks
| Benchmark | K-Exaone | Kimi K2.7 Code | Result |
|---|---|---|---|
| AA-IFBenchSource | 64.7% | 63.1% | K-Exaone leads |
Frequently Asked Questions (3)
Can I compare K-Exaone and Kimi K2.7 Code 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 Kimi K2.7 Code today?
Kimi K2.7 Code: $0.95 input / $4.00 output per 1M tokens Both model pages still include creator, context window, reasoning mode, and other metadata while benchmark coverage fills in.
Self-host vs API cost
Estimates at 50,000 req/day · 1000 tokens/req average.
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