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kimi-k2.5

Kimi K2.5 is Moonshot AI's native multimodal model, delivering state-of-the-art visual coding capability and a self-directed agent swarm paradigm. Built on Kimi K2 with continued pretraining over approximately 15T mixed visual and text tokens, it delivers strong performance in general reasoning, visual coding, and agentic tool-calling.

👁Vision🧠Reasoning🔧Tool calling⚡Caching
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Specifications

Context window262K tokens
Max output262K tokens
API typechat
AddedFeb 5, 2026
Model IDmoonshot/kimi-k2.5
Data retentionYes
Used for trainingUnknown
Provider location🇨🇳 China
Privacy policyMoonshot 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 Moonshot AI models overview.

Pricing

Input / 1M
$0.60
Output / 1M
$3.00
Cache write / 1M
$0.60
Cache read / 1M
$0.10
Estimated cost
100K input + 10K output$0.0900
1M input + 100K output$0.90
10M input + 1M output$9.00

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-k2.5.

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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-k2.5",
    messages=[
        {"role": "user", "content": "Explain quantum computing in one paragraph."},
    ],
)

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

Other Moonshot AI models

kimi-k2.6
262K ctx$0.95/1M
kimi-k2-thinking-turbo
131K ctx$0.60/1M
kimi-k2-0905-preview
131K ctx$0.60/1M
kimi-k2-thinking
131K ctx$0.60/1M
kimi-k2-turbo-preview
131K ctx$1.20/1M
kimi-k2-0711-preview
131K ctx$0.60/1M

Frequently asked questions

How much does kimi-k2.5 cost?
kimi-k2.5 is priced at $0.60 per million input tokens and $3.00 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-k2.5?
kimi-k2.5 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-k2.5 do?
kimi-k2.5 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-k2.5 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-k2.5". The Quickstart above shows Python, JavaScript and cURL snippets.

Access kimi-k2.5 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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