MOONSHOT AI VS ALIBABA
Kimi K2 Thinking vs Qwen3 Max
Kimi K2 Thinking is about 2.2x cheaper than Qwen3 Max on a blended 3:1 input:output rate — the same 10K-in/2K-out request costs $0.011 vs $0.024. Kimi K2 Thinking has the larger context window (262,144 vs 252,000 tokens).
Pricing verified
API pricing per 1M tokens
| Model | Input / 1M tokens | Output / 1M tokens | Blended (3:1 mix) |
|---|---|---|---|
| Kimi K2 Thinking | $0.60 | $2.50 | $1.075 |
| Qwen3 Max | $1.20 | $6.00 | $2.40 |
Rates from official Moonshot AI pricing and official Alibaba pricing, checked 2026-08-11.
What a real workload costs
Example: one request with 10,000 input tokens and 2,000 output tokens, then that request at 100,000 runs per month.
| Model | Per request (10K in / 2K out) | Per month (100K requests) | Monthly delta |
|---|---|---|---|
| Kimi K2 Thinking | $0.011 | $1,100 | — |
| Qwen3 Max | $0.024 | $2,400 | +$1,300 |
Model your own prompt sizes and volumes in the token cost analyzer, or check caching savings with the prompt caching calculator.
Specs side by side
| Spec | Kimi K2 Thinking | Qwen3 Max |
|---|---|---|
| Provider | Moonshot AI | Alibaba |
| Context window | 262,144 tokens | 252,000 tokens |
| Model class | Reasoning | Reasoning |
| Tokenizer | Proprietary (counts estimated) | qwen (exact, public) |
Count tokens for each model on its own page: Kimi K2 Thinking token counter and Qwen3 Max token counter. All Moonshot AI models are on the Kimi Token Counter. All Alibaba models are on the Qwen Token Counter.
FAQ
Kimi K2 Thinking vs Qwen3 Max FAQ
Which is cheaper, Kimi K2 Thinking or Qwen3 Max?
Kimi K2 Thinking is cheaper. At rates checked 2026-08-11, Kimi K2 Thinking costs $0.60 input / $2.50 output per 1M tokens, while Qwen3 Max costs $1.20 input / $6.00 output — about a 2.2x difference on a typical 3:1 input-heavy workload.
How much does a real request cost on Kimi K2 Thinking vs Qwen3 Max?
A request with 10,000 input tokens and 2,000 output tokens costs about $0.011 on Kimi K2 Thinking and $0.024 on Qwen3 Max. At 100,000 such requests per month that is $1,100 vs $2,400 — a difference of $1,300 per month.
Which has the bigger context window, Kimi K2 Thinking or Qwen3 Max?
Kimi K2 Thinking. It supports 262,144 tokens of context versus 252,000 tokens — roughly 197,000 English words in one request.
Do Kimi K2 Thinking and Qwen3 Max count tokens the same way?
Not exactly. Kimi K2 Thinking uses a proprietary tokenizer (counts are estimates) and Qwen3 Max uses the published qwen tokenizer. The same prompt will tokenize differently, which shifts effective cost per word.