OPENAI VS MOONSHOT AI

GPT-5.6 Terra vs Kimi K2.6

Kimi K2.6 is about 2.6x cheaper than GPT-5.6 Terra on a blended 3:1 input:output rate — the same 10K-in/2K-out request costs $0.0175 vs $0.044. GPT-5.6 Terra has the larger context window (1,047,576 vs 262,144 tokens).

Pricing verified

API pricing per 1M tokens

ModelInput / 1M tokensOutput / 1M tokensBlended (3:1 mix)
GPT-5.6 Terra$2.00$12.00$4.50
Kimi K2.6$0.95$4.00$1.713

Rates from official OpenAI 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
GPT-5.6 Terra$0.044$4,400+$2,650
Kimi K2.6$0.0175$1,750—

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

SpecGPT-5.6 TerraKimi K2.6
ProviderOpenAIMoonshot AI
Context window1,047,576 tokens262,144 tokens
Model classGeneral textGeneral text
Tokenizero200k_base (exact, public)Proprietary (counts estimated)

Count tokens for each model on its own page: GPT-5.6 Terra token counter and Kimi K2.6 token counter. All OpenAI models are on the OpenAI Token Counter. All Moonshot AI models are on the Kimi Token Counter.

FAQ

GPT-5.6 Terra vs Kimi K2.6 FAQ

Which is cheaper, GPT-5.6 Terra or Kimi K2.6?

Kimi K2.6 is cheaper. At rates checked 2026-08-11, GPT-5.6 Terra costs $2.00 input / $12.00 output per 1M tokens, while Kimi K2.6 costs $0.95 input / $4.00 output — about a 2.6x difference on a typical 3:1 input-heavy workload.

How much does a real request cost on GPT-5.6 Terra vs Kimi K2.6?

A request with 10,000 input tokens and 2,000 output tokens costs about $0.044 on GPT-5.6 Terra and $0.0175 on Kimi K2.6. At 100,000 such requests per month that is $4,400 vs $1,750 — a difference of $2,650 per month.

Which has the bigger context window, GPT-5.6 Terra or Kimi K2.6?

GPT-5.6 Terra. It supports 1,047,576 tokens of context versus 262,144 tokens — roughly 786,000 English words in one request.

Do GPT-5.6 Terra and Kimi K2.6 count tokens the same way?

Not exactly. GPT-5.6 Terra uses the published o200k_base tokenizer and Kimi K2.6 uses a proprietary tokenizer (counts are estimates). The same prompt will tokenize differently, which shifts effective cost per word.