MOONSHOT AI VS ALIBABA

Kimi K2.6 vs Qwen3.5 Plus

Qwen3.5 Plus is about 1.9x cheaper than Kimi K2.6 on a blended 3:1 input:output rate — the same 10K-in/2K-out request costs $0.0088 vs $0.0175. Qwen3.5 Plus has the larger context window (1,000,000 vs 262,144 tokens).

Pricing verified

API pricing per 1M tokens

ModelInput / 1M tokensOutput / 1M tokensBlended (3:1 mix)
Kimi K2.6$0.95$4.00$1.713
Qwen3.5 Plus$0.40$2.40$0.90

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.

ModelPer request (10K in / 2K out)Per month (100K requests)Monthly delta
Kimi K2.6$0.0175$1,750+$870
Qwen3.5 Plus$0.0088$880—

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

SpecKimi K2.6Qwen3.5 Plus
ProviderMoonshot AIAlibaba
Context window262,144 tokens1,000,000 tokens
Model classGeneral textGeneral text
TokenizerProprietary (counts estimated)Proprietary (counts estimated)

Count tokens for each model on its own page: Kimi K2.6 token counter and Qwen3.5 Plus token counter. All Moonshot AI models are on the Kimi Token Counter. All Alibaba models are on the Qwen Token Counter.

FAQ

Kimi K2.6 vs Qwen3.5 Plus FAQ

Which is cheaper, Kimi K2.6 or Qwen3.5 Plus?

Qwen3.5 Plus is cheaper. At rates checked 2026-08-11, Kimi K2.6 costs $0.95 input / $4.00 output per 1M tokens, while Qwen3.5 Plus costs $0.40 input / $2.40 output — about a 1.9x difference on a typical 3:1 input-heavy workload.

How much does a real request cost on Kimi K2.6 vs Qwen3.5 Plus?

A request with 10,000 input tokens and 2,000 output tokens costs about $0.0175 on Kimi K2.6 and $0.0088 on Qwen3.5 Plus. At 100,000 such requests per month that is $1,750 vs $880 — a difference of $870 per month.

Which has the bigger context window, Kimi K2.6 or Qwen3.5 Plus?

Qwen3.5 Plus. It supports 1,000,000 tokens of context versus 262,144 tokens — roughly 750,000 English words in one request.

Do Kimi K2.6 and Qwen3.5 Plus count tokens the same way?

Not exactly. Kimi K2.6 uses a proprietary tokenizer (counts are estimates) and Qwen3.5 Plus uses a proprietary tokenizer (counts are estimates). The same prompt will tokenize differently, which shifts effective cost per word.