DeepSeek V4-Pro vs Kimi K2.7 Code
Detailed pricing comparison and cost analysis.
Updated September 2026
Cost Simulator
| Feature | DeepSeek V4-Pro | Kimi K2.7 Code |
|---|---|---|
| Provider | DeepSeek | Moonshot AI |
| Input Price (1M) | $1.32 | $0.95 |
| Output Price (1M) | $3.96 | $4.00 |
| Context Window | 1,000,000 | 262,144 |
Verdict
DeepSeek V4-Pro costs $1.32 per 1M input tokens and $3.96 per 1M output tokens. Kimi K2.7 Code costs $0.95 per 1M input tokens and $4.00 per 1M output tokens. Kimi K2.7 Code is 28% cheaper on input tokens than DeepSeek V4-Pro. For output tokens, DeepSeek V4-Pro is the more affordable option at $3.96/1M vs $4.00.
On context window, DeepSeek V4-Pro supports 1,000,000 tokens — meaning it can fit more conversation history, documents, or code in a single request. This matters for RAG pipelines, long document analysis, and agentic workflows where context builds up over many turns.
When to choose DeepSeek V4-Pro
- ✓ Your workload is output-heavy — DeepSeek V4-Pro generates text cheaper
- ✓ You need a larger context window (1,000,000 tokens)
- ✓ You are already integrated with DeepSeek
When to choose Kimi K2.7 Code
- ✓ You need the lowest input token cost ($ 0.95/1M)
- ✓ You are already integrated with Moonshot AI
Use the calculator above to simulate your specific workload and find the exact break-even point. For most applications, the cheapest model is the one that minimises your total monthly bill given your input-to-output token ratio.
Frequently Asked Questions
Is DeepSeek V4-Pro cheaper than Kimi K2.7 Code? ▼
Kimi K2.7 Code is cheaper on input tokens at $0.95/1M vs $1.32/1M for DeepSeek V4-Pro — a 28% saving.
What is the context window of DeepSeek V4-Pro vs Kimi K2.7 Code? ▼
DeepSeek V4-Pro has a 1,000,000-token context window. Kimi K2.7 Code has a 262,144-token context window. DeepSeek V4-Pro supports the larger context, suitable for longer documents and agentic workflows.
Which model is better: DeepSeek V4-Pro or Kimi K2.7 Code? ▼
The best choice depends on your use case. For cost efficiency on input tokens, Kimi K2.7 Code is the cheaper option. For maximum context length, DeepSeek V4-Pro supports 1,000,000 tokens. Use the comparison table above to find the right fit for your workload.