qwen3.7-plus vs kimi-k3
Side-by-side comparison of qwen3.7-plus and kimi-k3: benchmarks, pricing, context window and capabilities. Both are accessible through Requesty's unified API. kimi-k3 outperforms qwen3.7-plus on 5 of 5 shared benchmarks.
qwen3.7-plus
Input / 1M
$0.40$0.32
Output / 1M
$1.60$1.28
Context
1.0M
Model ID
alibaba/qwen3.7-plus
kimi-k3
Input / 1M
$3.00
Output / 1M
$15.00
Context
1.0M
Model ID
moonshot/kimi-k3
Benchmark comparison
Intelligence Indexreasoning
qwen3.7-plus31.9%
kimi-k350.2%
Coding Indexcoding
qwen3.7-plus55.9%
kimi-k376.2%
GPQA Diamondreasoning
qwen3.7-plus90.0%
kimi-k393.5%
Terminal-Bench Hardagentic
qwen3.7-plus47.0%
kimi-k3N/A
τ²-Benchagentic
qwen3.7-plus93.0%
kimi-k3N/A
SciCodecoding
qwen3.7-plus46.1%
kimi-k359.5%
Humanity's Last Examreasoning
qwen3.7-plus35.6%
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
| qwen3.7-plus | kimi-k3 | |
|---|---|---|
| Input price / 1M | $0.40$0.32 | $3.00 |
| Output price / 1M | $1.60$1.28 | $15.00 |
| Context window | 1.0M tokens | 1.0M tokens |
| Max output | 131K tokens | 1.0M tokens |
| Vision input | Yes | Yes |
| Tool calling | Yes | Yes |
| Reasoning | Yes | Yes |
| Prompt caching | Yes | Yes |
| Computer use | N/A | N/A |
| Provider | Alibaba Cloud | Moonshot AI |
Questions people ask
Is qwen3.7-plus better than kimi-k3?
kimi-k3 outperforms qwen3.7-plus on 5 of 5 shared benchmarks. See the benchmark comparison above for specifics: qwen3.7-plus and kimi-k3 have different strengths across reasoning, coding, math and multimodal tasks.
Which is cheaper, qwen3.7-plus or kimi-k3?
qwen3.7-plus is cheaper. qwen3.7-plus costs $0.32/$1.28 per 1M input/output tokens, while kimi-k3 costs $3.00/$15.00. The prices shown are what you pay: qwen3.7-plus runs at 20% off its list rate of $0.40 per 1M input and $1.60 per 1M output.
Can I use qwen3.7-plus 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 "alibaba/qwen3.7-plus" and "moonshot/kimi-k3", no other code changes needed.
What are the context windows?
qwen3.7-plus supports up to 1.0M 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 qwen3.7-plus 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.