Requesty

kimi-k2.6

Kimi K2.6 is Moonshot AI's next-generation multimodal model, designed for long-horizon coding, coding-driven UI/UX generation, and multi-agent orchestration. It handles complex end-to-end coding tasks across Python, Rust, and Go, and can convert prompts and visual inputs into production-ready interfaces. Its agent swarm architecture scales to hundreds of parallel sub-agents for autonomous task decomposition - delivering documents, websites, and spreadsheets in a single run without human oversight.

👁Vision🧠Reasoning🔧Tool callingCaching

Specifications

Context window262K tokens
Max output262K tokens
API typechat
AddedApr 20, 2026
Model IDmoonshot/kimi-k2.6
Data retentionYes
Used for trainingUnknown
Provider location🇨🇳 China

Benchmarks

Benchmarks haven't been published yet for this exact variant.

Some variants (region-specific deployments, highspeed tiers) share benchmarks with their base model — check the base model page or the Moonshot AI models overview.

Pricing

Input / 1M
$0.95
Output / 1M
$4.00
Cache write / 1M
$0.96
Cache read / 1M
$0.16
Estimated cost
100K input + 10K output$0.14
1M input + 100K output$1.35
10M input + 1M output$13.50

Requesty charges exactly what the upstream provider charges — no markup, no per-request fees. Prompt caching and smart routing can reduce effective cost by 30-80%.

Quickstart

Drop-in compatible with the OpenAI SDK. Change the base URL, swap in your Requesty API key, and set the model to moonshot/kimi-k2.6.

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from openai import OpenAI client = OpenAI( api_key="YOUR_REQUESTY_API_KEY", base_url="https://router.requesty.ai/v1", ) response = client.chat.completions.create( model="moonshot/kimi-k2.6", messages=[ {"role": "user", "content": "Explain quantum computing in one paragraph."}, ], ) print(response.choices[0].message.content)

Other Moonshot AI models

Frequently asked questions

How much does kimi-k2.6 cost?
kimi-k2.6 is priced at $0.95 per million input tokens and $4.00 per million output tokens when accessed via Requesty. Prompt caching is supported, which can cut effective input cost by up to 90% on repeated context. Requesty charges exactly what the upstream provider charges — we don't add markup.
What is the context window of kimi-k2.6?
kimi-k2.6 has a context window of 262K tokens, with a maximum output of 262K tokens per response. That's roughly 350 words of input you can fit in a single prompt.
What can kimi-k2.6 do?
kimi-k2.6 supports vision input, tool calling, extended reasoning, prompt caching. You can call it through any OpenAI-compatible client by pointing base_url to Requesty.
How do I use kimi-k2.6 with the OpenAI SDK?
Install the OpenAI SDK, set base_url to "https://router.requesty.ai/v1", set your API key to your Requesty key, and set the model to "moonshot/kimi-k2.6". The Quickstart above shows Python, JavaScript and cURL snippets.

Access kimi-k2.6 through Requesty

One API key, 400+ models, OpenAI-compatible. No markup on provider prices, automatic failover, and smart caching built-in.