deepseek-v4-flash-0731 vs kimi-k2.5
Side-by-side comparison of deepseek-v4-flash-0731 and kimi-k2.5: benchmarks, pricing, context window and capabilities. Both are accessible through Requesty's unified API. deepseek-v4-flash-0731 outperforms kimi-k2.5 on 4 of 4 shared benchmarks.
deepseek-v4-flash-0731
Input / 1M
$0.44
Output / 1M
$1.32
Context
1M
Model ID
deepseek/deepseek-v4-flash-0731
kimi-k2.5
Input / 1M
$0.60
Output / 1M
$3.00
Context
262K
Model ID
moonshot/kimi-k2.5
Benchmark comparison
Intelligence Indexreasoning
deepseek-v4-flash-073140.8%
kimi-k2.527.6%
Coding Indexcoding
deepseek-v4-flash-073169.1%
kimi-k2.546.8%
GPQA Diamondreasoning
deepseek-v4-flash-073190.8%
kimi-k2.587.9%
Terminal-Bench Hardagentic
deepseek-v4-flash-0731N/A
kimi-k2.534.8%
τ²-Benchagentic
deepseek-v4-flash-0731N/A
kimi-k2.595.9%
SciCodecoding
deepseek-v4-flash-073150.3%
kimi-k2.5N/A
Humanity's Last Examreasoning
deepseek-v4-flash-073138.6%
kimi-k2.530.7%
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-k2.5 | |
|---|---|---|
| Input price / 1M | $0.44 | $0.60 |
| Output price / 1M | $1.32 | $3.00 |
| 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-flash-0731 better than kimi-k2.5?
deepseek-v4-flash-0731 outperforms kimi-k2.5 on 4 of 4 shared benchmarks. See the benchmark comparison above for specifics: deepseek-v4-flash-0731 and kimi-k2.5 have different strengths across reasoning, coding, math and multimodal tasks.
Which is cheaper, deepseek-v4-flash-0731 or kimi-k2.5?
deepseek-v4-flash-0731 is cheaper. deepseek-v4-flash-0731 costs $0.44/$1.32 per 1M input/output tokens, while kimi-k2.5 costs $0.60/$3.00.
Can I use deepseek-v4-flash-0731 and kimi-k2.5 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-k2.5", no other code changes needed.
What are the context windows?
deepseek-v4-flash-0731 supports up to 1M tokens of context. kimi-k2.5 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-flash-0731 and kimi-k2.5 with one line of code
Requesty provides a single OpenAI-compatible API for 600+ models. Change the model parameter, not your code.