MISTRAL VS MOONSHOT AI

Magistral Medium vs Kimi K2.6

Kimi K2.6 is about 1.6x cheaper than Magistral Medium on a blended 3:1 input:output rate — the same 10K-in/2K-out request costs $0.0175 vs $0.03. Kimi K2.6 has the larger context window (262,144 vs 128,000 tokens).

Pricing verified

API pricing per 1M tokens

ModelInput / 1M tokensOutput / 1M tokensBlended (3:1 mix)
Magistral Medium$2.00$5.00$2.75
Kimi K2.6$0.95$4.00$1.713

Rates from official Mistral 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
Magistral Medium$0.03$3,000+$1,250
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

SpecMagistral MediumKimi K2.6
ProviderMistralMoonshot AI
Context window128,000 tokens262,144 tokens
Model classReasoningGeneral text
TokenizerProprietary (counts estimated)Proprietary (counts estimated)

Count tokens for each model on its own page: Magistral Medium token counter and Kimi K2.6 token counter. All Mistral models are on the Mistral Token Counter. All Moonshot AI models are on the Kimi Token Counter.

FAQ

Magistral Medium vs Kimi K2.6 FAQ

Which is cheaper, Magistral Medium or Kimi K2.6?

Kimi K2.6 is cheaper. At rates checked 2026-08-11, Magistral Medium costs $2.00 input / $5.00 output per 1M tokens, while Kimi K2.6 costs $0.95 input / $4.00 output — about a 1.6x difference on a typical 3:1 input-heavy workload.

How much does a real request cost on Magistral Medium vs Kimi K2.6?

A request with 10,000 input tokens and 2,000 output tokens costs about $0.03 on Magistral Medium and $0.0175 on Kimi K2.6. At 100,000 such requests per month that is $3,000 vs $1,750 — a difference of $1,250 per month.

Which has the bigger context window, Magistral Medium or Kimi K2.6?

Kimi K2.6. It supports 262,144 tokens of context versus 128,000 tokens — roughly 197,000 English words in one request.

Do Magistral Medium and Kimi K2.6 count tokens the same way?

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