DeepSeek V3.1 vs Kimi K2.5
Side-by-side comparison of specs, pricing, and capabilities
| Spec | 🧠 DeepSeek V3.1 | 🧠 Kimi K2.5 |
|---|---|---|
| Provider | DeepSeek | Moonshot AI |
| Category | 🧠 Reasoning | 🧠 Reasoning |
| Parameters | 671B | 1.0T |
| Context Window | 128K tokens | 128K tokens |
| License | 🔓 open | 🔓 open |
| Input Price | $0.27 | $0.60 |
| Output Price | $1.10 | $2.40 |
| API Available | ✅ | ✅ |
| Released | Jun 1, 2025 | Jul 1, 2025 |
| Trending Score | 🔥 88 | 🔥 81 |
DeepSeek V3.1 Strengths
- ✓Incredible cost efficiency
- ✓Open weights
- ✓Top-tier math/coding
- ✓MoE architecture
Kimi K2.5 Strengths
- ✓1T+ parameters (MoE)
- ✓Open weights
- ✓Strong reasoning
- ✓Good coding
About DeepSeek V3.1
671B MoE model with only 37B active parameters. Open-weight, excels at math, coding, and Chinese language tasks.
View full details →About Kimi K2.5
1T+ MoE architecture with strong long-context and multi-step reasoning. Open weights, competitive with top models.
View full details →❓ Frequently Asked Questions
Which is better, DeepSeek V3.1 or Kimi K2.5?
It depends on your use case. DeepSeek V3.1 (DeepSeek) has a trending score of 88, while Kimi K2.5 (Moonshot AI) scores 81. DeepSeek V3.1 costs $0.27 per 1M input tokens. Check the comparison table above for detailed specs.
Is DeepSeek V3.1 cheaper than Kimi K2.5?
DeepSeek V3.1 costs $0.27 input / $1.10 output per 1M tokens, while Kimi K2.5 costs $0.60 input / $2.40 output.
Can I use both DeepSeek V3.1 and Kimi K2.5?
Yes! Many developers use multiple models for different tasks. You might use one for complex reasoning and another for high-volume, cost-sensitive workloads.