DeepSeek-V3.2 (Thinking) vs Kimi K2-Thinking-0905: Specs & Benchmark Comparison
| Characteristic | DeepSeek-V3.2 (Thinking) | Kimi K2-Thinking-0905 |
|---|---|---|
| Company | DeepSeek | Moonshot AI |
| Release Date | November 30, 2025 | September 4, 2025 |
| Parameters | 685B | 1.0T |
| Multimodal | No | No |
| Context (input) | 131K | 262K |
| Context (output) | 66K | 66K |
| Input Price / 1M | $0.28 | $0.60 |
| Output Price / 1M | $0.42 | $2.40 |
| Average Score | 0.9 | 0.9 |
| Benchmarks | ||
| AIME 2025 | 0.9 | 1.0 |
| HMMT 2025 | 0.9 | 1.0 |
| GPQA | 0.8 | 0.8 |
| MMLU-Pro | 0.8 | 0.8 |
Visual Benchmark Comparison
DeepSeek-V3.2 (Thinking)
Kimi K2-Thinking-0905
AIME 20250.9 vs 1.0
0.9
1.0
HMMT 20250.9 vs 1.0
0.9
1.0
GPQA0.8 vs 0.8
0.8
0.8
MMLU-Pro0.8 vs 0.8
0.8
0.8
Verdict
DeepSeek-V3.2 (Thinking) leads in 2 out of 4 comparison categories.
Overall Performance
Both models show comparable average scores: DeepSeek-V3.2 (Thinking) — 0.9, Kimi K2-Thinking-0905 — 0.9.
API Cost
DeepSeek-V3.2 (Thinking) is 4.3x cheaper: input $0.28/1M vs $0.60/1M tokens.
Context Window
Kimi K2-Thinking-0905 supports a larger context: 262K vs 131K tokens.
Recency
DeepSeek-V3.2 (Thinking) is newer: released 11/30/2025 vs 9/4/2025.
More About These Models
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The DeepSeek-V3.2 (Thinking) 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 DeepSeek-V3.2 (Thinking) or Kimi K2-Thinking-0905 page. See also the complete list of AI model comparisons.