qwen3-max vs kimi-k2.7-code
Side-by-side comparison of qwen3-max and kimi-k2.7-code: benchmarks, pricing, context window and capabilities. Both are accessible through Requesty's unified API.
qwen3-max
Input / 1M
$0.86
Output / 1M
$3.44
Context
262K
Model ID
alibaba/qwen3-max
kimi-k2.7-code
Input / 1M
$0.95
Output / 1M
$4.00
Context
262K
Model ID
moonshot/kimi-k2.7-code
Benchmark comparison
Intelligence Indexreasoning
qwen3-max39.8%
kimi-k2.7-codeN/A
Coding Indexcoding
qwen3-max30.5%
kimi-k2.7-codeN/A
GPQA Diamondreasoning
qwen3-max86.1%
kimi-k2.7-codeN/A
Terminal-Bench Hardagentic
qwen3-max24.2%
kimi-k2.7-codeN/A
τ²-Benchagentic
qwen3-max83.6%
kimi-k2.7-codeN/A
SciCodecoding
qwen3-max43.1%
kimi-k2.7-codeN/A
Humanity's Last Examreasoning
qwen3-max26.2%
kimi-k2.7-codeN/A
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-max | kimi-k2.7-code | |
|---|---|---|
| Input price / 1M | $0.86 | $0.95 |
| Output price / 1M | $3.44 | $4.00 |
| Context window | 262K tokens | 262K tokens |
| Max output | 66K tokens | 262K tokens |
| Vision input | Yes | Yes |
| Tool calling | Yes | Yes |
| Reasoning | N/A | Yes |
| Prompt caching | Yes | Yes |
| Computer use | N/A | N/A |
| Provider | Alibaba Cloud | Moonshot AI |
Questions people ask
Is qwen3-max better than kimi-k2.7-code?
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, qwen3-max or kimi-k2.7-code?
qwen3-max is cheaper. qwen3-max costs $0.86/$3.44 per 1M input/output tokens, while kimi-k2.7-code costs $0.95/$4.00.
Can I use qwen3-max and kimi-k2.7-code 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-max" and "moonshot/kimi-k2.7-code", no other code changes needed.
What are the context windows?
qwen3-max supports up to 262K tokens of context. kimi-k2.7-code 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 qwen3-max and kimi-k2.7-code with one line of code
Requesty provides a single OpenAI-compatible API for 400+ models. Change the model parameter, not your code.
Get started free