deepseek-v4-pro vs kimi-k2.6
Side-by-side comparison of deepseek-v4-pro and kimi-k2.6: benchmarks, pricing, context window and capabilities. Both are accessible through Requesty's unified API. deepseek-v4-pro and kimi-k2.6 trade wins evenly across shared benchmarks.
deepseek-v4-pro
Input / 1M
$0.43
Output / 1M
$0.87
Context
1M
Model ID
deepseek/deepseek-v4-pro
kimi-k2.6
Input / 1M
$0.95
Output / 1M
$4.00
Context
262K
Model ID
moonshot/kimi-k2.6
Benchmark comparison
Intelligence Indexreasoning
deepseek-v4-pro44.3%
kimi-k2.644.2%
Coding Indexcoding
deepseek-v4-pro59.4%
kimi-k2.661.8%
GPQA Diamondreasoning
deepseek-v4-pro88.8%
kimi-k2.691.1%
Terminal-Bench Hardagentic
deepseek-v4-pro46.2%
kimi-k2.643.9%
τ²-Benchagentic
deepseek-v4-pro96.2%
kimi-k2.695.9%
SciCodecoding
deepseek-v4-pro50.0%
kimi-k2.653.5%
Humanity's Last Examreasoning
deepseek-v4-pro35.9%
kimi-k2.635.9%
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-k2.6 | |
|---|---|---|
| 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-k2.6?
deepseek-v4-pro and kimi-k2.6 trade wins evenly across shared benchmarks. See the benchmark comparison above for specifics: deepseek-v4-pro and kimi-k2.6 have different strengths across reasoning, coding, math and multimodal tasks.
Which is cheaper, deepseek-v4-pro or kimi-k2.6?
deepseek-v4-pro is cheaper. deepseek-v4-pro costs $0.43/$0.87 per 1M input/output tokens, while kimi-k2.6 costs $0.95/$4.00.
Can I use deepseek-v4-pro and kimi-k2.6 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-k2.6", no other code changes needed.
What are the context windows?
deepseek-v4-pro supports up to 1M tokens of context. kimi-k2.6 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-k2.6 with one line of code
Requesty provides a single OpenAI-compatible API for 400+ models. Change the model parameter, not your code.