Requesty
Inceptron AB

kimi-k2.6

Kimi K2.6 is Moonshot AI's latest open weight reasoning model, built for long horizon coding, agentic execution, and multimodal reasoning. It retains the trillion parameter MoE architecture with roughly 32B active parameters and a 256k token context window, while improving agentic benchmark performance and knowledge reliability over K2.5. Native text, image, and video input plus tool driven workflows make it well suited for coding, research, and complex multi step tasks.

👁Vision🧠Reasoning🔧Tool calling⚡Caching
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Specifications

Context window262K tokens
Max output262K tokens
API typechat
AddedApr 29, 2026
Model IDinceptron/kimi-k2.6
Data retentionNo
Used for trainingNo
Provider location🇪🇺 EU (Sweden)
Privacy policyInceptron Privacy Policy →

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 Inceptron AB models overview.

Pricing

Input / 1M
$0.80
Output / 1M
$3.50
Cache write
—
Cache read / 1M
$0.20
Estimated cost
100K input + 10K output$0.11
1M input + 100K output$1.15
10M input + 1M output$11.50

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 inceptron/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="inceptron/kimi-k2.6",
    messages=[
        {"role": "user", "content": "Explain quantum computing in one paragraph."},
    ],
)

print(response.choices[0].message.content)

Other Inceptron AB models

minimax-m2.5
197K ctx$0.28/1M
glm-5.1
203K ctx$1.40/1M

Frequently asked questions

How much does kimi-k2.6 cost?
kimi-k2.6 is priced at $0.80 per million input tokens and $3.50 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 "inceptron/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.

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