XAI VS MOONSHOT AI

Grok 4.3 vs Kimi K2 Thinking

Kimi K2 Thinking is about 1.5x cheaper than Grok 4.3 on a blended 3:1 input:output rate — the same 10K-in/2K-out request costs $0.011 vs $0.0175. Grok 4.3 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)
Grok 4.3$1.25$2.50$1.563
Kimi K2 Thinking$0.60$2.50$1.075

Rates from official xAI pricing and official Moonshot AI 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
Grok 4.3$0.0175$1,750+$650
Kimi K2 Thinking$0.011$1,100—

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

SpecGrok 4.3Kimi K2 Thinking
ProviderxAIMoonshot AI
Context window1,000,000 tokens262,144 tokens
Model classReasoningReasoning
TokenizerProprietary (counts estimated)Proprietary (counts estimated)

Count tokens for each model on its own page: Grok 4.3 token counter and Kimi K2 Thinking token counter. All xAI models are on the Grok Token Counter. All Moonshot AI models are on the Kimi Token Counter.

FAQ

Grok 4.3 vs Kimi K2 Thinking FAQ

Which is cheaper, Grok 4.3 or Kimi K2 Thinking?

Kimi K2 Thinking is cheaper. At rates checked 2026-08-11, Grok 4.3 costs $1.25 input / $2.50 output per 1M tokens, while Kimi K2 Thinking costs $0.60 input / $2.50 output — about a 1.5x difference on a typical 3:1 input-heavy workload.

How much does a real request cost on Grok 4.3 vs Kimi K2 Thinking?

A request with 10,000 input tokens and 2,000 output tokens costs about $0.0175 on Grok 4.3 and $0.011 on Kimi K2 Thinking. At 100,000 such requests per month that is $1,750 vs $1,100 — a difference of $650 per month.

Which has the bigger context window, Grok 4.3 or Kimi K2 Thinking?

Grok 4.3. It supports 1,000,000 tokens of context versus 262,144 tokens — roughly 750,000 English words in one request.

Do Grok 4.3 and Kimi K2 Thinking count tokens the same way?

Not exactly. Grok 4.3 uses a proprietary tokenizer (counts are estimates) and Kimi K2 Thinking uses a proprietary tokenizer (counts are estimates). The same prompt will tokenize differently, which shifts effective cost per word.