deepseek-v4-flash-0731 vs kimi-k3
Side-by-side comparison of deepseek-v4-flash-0731 and kimi-k3: benchmarks, pricing, context window and capabilities. Both are accessible through Requesty's unified API. kimi-k3 outperforms deepseek-v4-flash-0731 on 5 of 5 shared benchmarks.
deepseek-v4-flash-0731
Input / 1M
$0.44
Output / 1M
$1.32
Context
1M
Model ID
deepseek/deepseek-v4-flash-0731
kimi-k3
Input / 1M
$3.00
Output / 1M
$15.00
Context
1.0M
Model ID
moonshot/kimi-k3
Benchmark comparison
Intelligence Indexreasoning
deepseek-v4-flash-073140.8%
kimi-k350.2%
Coding Indexcoding
deepseek-v4-flash-073169.1%
kimi-k376.2%
GPQA Diamondreasoning
deepseek-v4-flash-073190.8%
kimi-k393.5%
SciCodecoding
deepseek-v4-flash-073150.3%
kimi-k359.5%
Humanity's Last Examreasoning
deepseek-v4-flash-073138.6%
kimi-k346.9%
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-flash-0731 | kimi-k3 | |
|---|---|---|
| Input price / 1M | $0.44 | $3.00 |
| Output price / 1M | $1.32 | $15.00 |
| Context window | 1M tokens | 1.0M tokens |
| Max output | 384K tokens | 1.0M 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-flash-0731 better than kimi-k3?
kimi-k3 outperforms deepseek-v4-flash-0731 on 5 of 5 shared benchmarks. See the benchmark comparison above for specifics: deepseek-v4-flash-0731 and kimi-k3 have different strengths across reasoning, coding, math and multimodal tasks.
Which is cheaper, deepseek-v4-flash-0731 or kimi-k3?
deepseek-v4-flash-0731 is cheaper. deepseek-v4-flash-0731 costs $0.44/$1.32 per 1M input/output tokens, while kimi-k3 costs $3.00/$15.00.
Can I use deepseek-v4-flash-0731 and kimi-k3 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-flash-0731" and "moonshot/kimi-k3", no other code changes needed.
What are the context windows?
deepseek-v4-flash-0731 supports up to 1M tokens of context. kimi-k3 supports up to 1.0M 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-flash-0731 and kimi-k3 with one line of code
Requesty provides a single OpenAI-compatible API for 600+ models. Change the model parameter, not your code.