gemini-3.5-flash vs kimi-k2
Side-by-side comparison of gemini-3.5-flash and kimi-k2: benchmarks, pricing, context window and capabilities. Both are accessible through Requesty's unified API.
gemini-3.5-flash
Input / 1M
$1.50
Output / 1M
$9.00
Context
1.0M
Model ID
google/gemini-3.5-flash
kimi-k2
Input / 1M
$0.60
Output / 1M
$2.50
Context
262K
Model ID
vertex/kimi-k2
Pricing & specifications
| gemini-3.5-flash | kimi-k2 | |
|---|---|---|
| Input price / 1M | $1.50 | $0.60 |
| Output price / 1M | $9.00 | $2.50 |
| Context window | 1.0M tokens | 262K tokens |
| Max output | 66K tokens | 262K tokens |
| Vision input | Yes | N/A |
| Tool calling | Yes | Yes |
| Reasoning | Yes | Yes |
| Prompt caching | Yes | Yes |
| Computer use | N/A | N/A |
| Provider | Google Gemini API | Google Vertex AI |
Questions people ask
Is gemini-3.5-flash better than kimi-k2?
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, gemini-3.5-flash or kimi-k2?
kimi-k2 is cheaper. gemini-3.5-flash costs $1.50/$9.00 per 1M input/output tokens, while kimi-k2 costs $0.60/$2.50.
Can I use gemini-3.5-flash and kimi-k2 through the same API?
Yes. Requesty provides a single OpenAI-compatible API that routes to both. Change just the "model" parameter to switch between "google/gemini-3.5-flash" and "vertex/kimi-k2", no other code changes needed.
What are the context windows?
gemini-3.5-flash supports up to 1.0M tokens of context. kimi-k2 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 gemini-3.5-flash and kimi-k2 with one line of code
Requesty provides a single OpenAI-compatible API for 600+ models. Change the model parameter, not your code.