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qwen3.7-max vs moonshotai/Kimi-K2.5

Side-by-side comparison of qwen3.7-max and moonshotai/Kimi-K2.5: benchmarks, pricing, context window and capabilities. Both are accessible through Requesty's unified API.

Pricing & specifications

qwen3.7-maxmoonshotai/Kimi-K2.5
Input price / 1M$2.50$0.45
Output price / 1M$7.50$2.25
Context window1.0M tokens262K tokens
Max output131K tokens131K tokens
Vision inputN/AYes
Tool callingYesYes
ReasoningYesYes
Prompt cachingYesYes
Computer useN/AN/A
ProviderAlibaba CloudDeepInfra

Questions people ask

Is qwen3.7-max better than moonshotai/Kimi-K2.5?
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, qwen3.7-max or moonshotai/Kimi-K2.5?
moonshotai/Kimi-K2.5 is cheaper. qwen3.7-max costs $2.50/$7.50 per 1M input/output tokens, while moonshotai/Kimi-K2.5 costs $0.45/$2.25.
Can I use qwen3.7-max and moonshotai/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 "alibaba/qwen3.7-max" and "deepinfra/moonshotai/Kimi-K2.5", no other code changes needed.
What are the context windows?
qwen3.7-max supports up to 1.0M tokens of context. moonshotai/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 qwen3.7-max and moonshotai/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.