K-EXAONE-236B-A23B vs Kimi K2-Thinking-0905: Specs & Benchmark Comparison
| Characteristic | K-EXAONE-236B-A23B | Kimi K2-Thinking-0905 |
|---|---|---|
| Company | LG AI Research | Moonshot AI |
| Release Date | December 30, 2025 | September 4, 2025 |
| Parameters | 236B | 1.0T |
| Multimodal | No | No |
| Context (input) | 33K | 262K |
| Context (output) | 33K | 66K |
| Input Price / 1M | $0.60 | $0.60 |
| Output Price / 1M | $1.00 | $2.40 |
| Average Score | 0.8 | 0.9 |
| Benchmarks | ||
| AIME 2025 | 0.9 | 1.0 |
| MMLU-Pro | 0.8 | 0.8 |
Visual Benchmark Comparison
K-EXAONE-236B-A23B
Kimi K2-Thinking-0905
AIME 20250.9 vs 1.0
0.9
1.0
MMLU-Pro0.8 vs 0.8
0.8
0.8
Verdict
K-EXAONE-236B-A23B leads in 2 out of 4 comparison categories.
Overall Performance
Both models show comparable average scores: K-EXAONE-236B-A23B — 0.8, Kimi K2-Thinking-0905 — 0.9.
API Cost
K-EXAONE-236B-A23B is 1.9x cheaper: input $0.60/1M vs $0.60/1M tokens.
Context Window
Kimi K2-Thinking-0905 supports a larger context: 262K vs 33K tokens.
Recency
K-EXAONE-236B-A23B is newer: released 12/30/2025 vs 9/4/2025.
More About These Models
Related Comparisons
The K-EXAONE-236B-A23B and Kimi K2-Thinking-0905 comparison is updated for 2026. Data includes benchmark results, API pricing, context window size and other specifications. For more detailed information, visit the K-EXAONE-236B-A23B or Kimi K2-Thinking-0905 page. See also the complete list of AI model comparisons.