DeepSeek-V3.2-Exp vs Kimi K2 0905: Specs & Benchmark Comparison
| Characteristic | DeepSeek-V3.2-Exp | Kimi K2 0905 |
|---|---|---|
| Company | DeepSeek | Moonshot AI |
| Release Date | September 28, 2025 | September 5, 2025 |
| Parameters | 685B | 1.0T |
| Multimodal | No | No |
| Context (input) | 164K | 262K |
| Context (output) | 66K | 262K |
| Input Price / 1M | $0.27 | $0.60 |
| Output Price / 1M | $0.41 | $2.50 |
| Average Score | 0.8 | 0.8 |
| Benchmarks | ||
| GPQA | 0.8 | 0.8 |
| MMLU-Pro | 0.8 | 0.8 |
Visual Benchmark Comparison
DeepSeek-V3.2-Exp
Kimi K2 0905
GPQA0.8 vs 0.8
0.8
0.8
MMLU-Pro0.8 vs 0.8
0.8
0.8
Verdict
DeepSeek-V3.2-Exp leads in 2 out of 4 comparison categories.
Overall Performance
Both models show comparable average scores: DeepSeek-V3.2-Exp — 0.8, Kimi K2 0905 — 0.8.
API Cost
DeepSeek-V3.2-Exp is 4.6x cheaper: input $0.27/1M vs $0.60/1M tokens.
Context Window
Kimi K2 0905 supports a larger context: 262K vs 164K tokens.
Recency
DeepSeek-V3.2-Exp is newer: released 9/28/2025 vs 9/5/2025.
More About These Models
Related Comparisons
Frequently Asked Questions
Which is better for coding — DeepSeek-V3.2-Exp or Kimi K2 0905?
Direct comparison on the SWE-Bench benchmark is not available. We recommend reviewing other metrics on the comparison page.
Which model is cheaper — DeepSeek-V3.2-Exp or Kimi K2 0905?
DeepSeek-V3.2-Exp is cheaper for input: $0.27 per 1M tokens vs $0.60.
Which has a larger context window — DeepSeek-V3.2-Exp or Kimi K2 0905?
Kimi K2 0905 supports a larger context: 262,144 tokens vs 163,840.
The DeepSeek-V3.2-Exp and Kimi K2 0905 comparison is updated for 2026. Data includes benchmark results, API pricing, context window size and other specifications. For more detailed information, visit the DeepSeek-V3.2-Exp or Kimi K2 0905 page. See also the complete list of AI model comparisons.