DeepSeek V4 Pro vs Kimi K2.5
How do these models stack up? Below is an expert side-by-side comparison of specifications, context window capacity, live pricing per million tokens, and standardized benchmark scores for DeepSeek V4 Pro and Kimi K2.5.
DeepSeek V4 Pro
DeepSeek V4 Pro is a large-scale Mixture-of-Experts model from DeepSeek with 1.6T total parameters and 49B activated parameters, supporting a 1M-token context window. It is designed for advanced reasoning, coding,...
Kimi K2.5
Kimi K2.5 is Moonshot AI's native multimodal model, delivering state-of-the-art visual coding capability and a self-directed agent swarm paradigm. Built on Kimi K2 with continued pretraining over approximately 15T mixed...
Technical Specifications
| Specification | DeepSeek V4 Pro | Kimi K2.5 |
|---|---|---|
| Provider | DeepSeek | Moonshot AI |
| Context Window | 1,048,576 tokens | 262,144 tokens |
| Agent Suitability | 94/100 | N/A |
| Time to First Token (TTFT) | 280 ms | N/A |
| Deployment Model | managed api | managed api |
| Production Stability | stable | stable |
| API Available | Yes | Yes |
| Released Date | 2026-04-24 | 2026-01-27 |
API Pricing Comparison
Input Price per Million Tokens
DeepSeek V4 Pro
$0.43
Kimi K2.5
$0.38
Output Price per Million Tokens
DeepSeek V4 Pro
$0.87
Kimi K2.5
$2.02
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Benchmark Performance Metrics
Scores show the raw performance percentages verified across key evaluation suites. Higher bars indicate superior accuracy and capability in that domain.
DeepSeek V4 Pro Quirks & Gotchas
- ▸MoE architecture — cold-start latency on first request, use keep-alive
- ▸Best cost-performance ratio of any frontier model — strong tool calling for agentic use
Kimi K2.5 Quirks & Gotchas
No developer gotchas reported.