K-EXAONE-236B-A23B vs MiniMax M2.7: Specs & Benchmark Comparison
| Characteristic | K-EXAONE-236B-A23B | MiniMax M2.7 |
|---|---|---|
| Company | LG AI Research | MiniMax |
| Release Date | December 30, 2025 | March 18, 2026 |
| Parameters | 236B | — |
| Multimodal | No | No |
| Context (input) | 33K | 205K |
| Context (output) | 33K | 100K |
| Input Price / 1M | $0.60 | $0.30 |
| Output Price / 1M | $1.00 | $1.20 |
| Average Score | 0.8 | 0.0 |
Verdict
MiniMax M2.7 leads in 3 out of 3 comparison categories.
API Cost
MiniMax M2.7 is 1.1x cheaper: input $0.30/1M vs $0.60/1M tokens.
Context Window
MiniMax M2.7 supports a larger context: 205K vs 33K tokens.
Recency
MiniMax M2.7 is newer: released 3/18/2026 vs 12/30/2025.
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The K-EXAONE-236B-A23B and MiniMax M2.7 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 MiniMax M2.7 page. See also the complete list of AI model comparisons.