K-EXAONE-236B-A23B vs Qwen3-235B-A22B-Thinking-2507: Specs & Benchmark Comparison
| Characteristic | K-EXAONE-236B-A23B | Qwen3-235B-A22B-Thinking-2507 |
|---|---|---|
| Company | LG AI Research | Alibaba |
| Release Date | December 30, 2025 | July 24, 2025 |
| Parameters | 236B | 235B |
| Multimodal | No | No |
| Context (input) | 33K | 256K |
| Context (output) | 33K | 131K |
| Input Price / 1M | $0.60 | $0.30 |
| Output Price / 1M | $1.00 | $3.00 |
| Average Score | 0.8 | 0.9 |
| Benchmarks | ||
| AIME 2025 | 0.9 | 0.9 |
Visual Benchmark Comparison
K-EXAONE-236B-A23B
Qwen3-235B-A22B-Thinking-2507
AIME 20250.9 vs 0.9
0.9
0.9
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, Qwen3-235B-A22B-Thinking-2507 — 0.9.
API Cost
K-EXAONE-236B-A23B is 2.1x cheaper: input $0.60/1M vs $0.30/1M tokens.
Context Window
Qwen3-235B-A22B-Thinking-2507 supports a larger context: 256K vs 33K tokens.
Recency
K-EXAONE-236B-A23B is newer: released 12/30/2025 vs 7/24/2025.
More About These Models
Related Comparisons
The K-EXAONE-236B-A23B and Qwen3-235B-A22B-Thinking-2507 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 Qwen3-235B-A22B-Thinking-2507 page. See also the complete list of AI model comparisons.