deepseek-v4-pro vs kimi-k2.7-code
Side-by-side comparison of deepseek-v4-pro and kimi-k2.7-code: benchmarks, pricing, context window and capabilities. Both are accessible through Requesty's unified API.
deepseek-v4-pro
Input / 1M
$0.43
Output / 1M
$0.87
Context
1M
Model ID
deepseek/deepseek-v4-pro
kimi-k2.7-code
Input / 1M
$0.95
Output / 1M
$4.00
Context
262K
Model ID
moonshot/kimi-k2.7-code
Benchmark comparison
Intelligence Indexreasoning
deepseek-v4-pro51.5%
kimi-k2.7-codeN/A
Coding Indexcoding
deepseek-v4-pro47.5%
kimi-k2.7-codeN/A
GPQA Diamondreasoning
deepseek-v4-pro88.8%
kimi-k2.7-codeN/A
Terminal-Bench Hardagentic
deepseek-v4-pro46.2%
kimi-k2.7-codeN/A
τ²-Benchagentic
deepseek-v4-pro96.2%
kimi-k2.7-codeN/A
SciCodecoding
deepseek-v4-pro50.0%
kimi-k2.7-codeN/A
Humanity's Last Examreasoning
deepseek-v4-pro35.9%
kimi-k2.7-codeN/A
Scores sourced from official model cards, Artificial Analysis, and public leaderboards. Benchmarks measure specific skills and don't capture every aspect of model quality.
Pricing & specifications
| deepseek-v4-pro | kimi-k2.7-code | |
|---|---|---|
| Input price / 1M | $0.43 | $0.95 |
| Output price / 1M | $0.87 | $4.00 |
| Context window | 1M tokens | 262K tokens |
| Max output | 384K tokens | 262K tokens |
| Vision input | N/A | Yes |
| Tool calling | Yes | Yes |
| Reasoning | N/A | Yes |
| Prompt caching | Yes | Yes |
| Computer use | N/A | N/A |
| Provider | DeepSeek | Moonshot AI |
Questions people ask
Is deepseek-v4-pro better than kimi-k2.7-code?
Benchmark data is limited for one or both models. Compare pricing and capabilities in the tables above, and test both on your own workload.
Which is cheaper, deepseek-v4-pro or kimi-k2.7-code?
deepseek-v4-pro is cheaper. deepseek-v4-pro costs $0.43/$0.87 per 1M input/output tokens, while kimi-k2.7-code costs $0.95/$4.00.
Can I use deepseek-v4-pro and kimi-k2.7-code through the same API?
Yes. Requesty provides a single OpenAI-compatible API that routes to both. Change just the "model" parameter to switch between "deepseek/deepseek-v4-pro" and "moonshot/kimi-k2.7-code", no other code changes needed.
What are the context windows?
deepseek-v4-pro supports up to 1M tokens of context. kimi-k2.7-code supports up to 262K tokens. Longer context means you can feed larger documents or codebases in a single prompt, though quality often degrades past 128K for most models.
Switch between deepseek-v4-pro and kimi-k2.7-code with one line of code
Requesty provides a single OpenAI-compatible API for 400+ models. Change the model parameter, not your code.
Get started free