Requesty
Parasail

kimi-k2.7-code

Kimi K2.7 Code is a coding-focused model in Moonshot AI's Kimi K2 family, built to complete end-to-end programming tasks reliably over long contexts. It uses a native multimodal mixture-of-experts architecture that accepts text and image input, and it always operates in a thinking mode, preserving full reasoning content across multi-turn conversations. With a 262K-token context window, it targets long-horizon coding, agentic task decomposition, and multi-turn dialogue. The model activates 32B parameters out of roughly 1T total.

VisionReasoningTool callingCachingJSON schema
Try kimi-k2.7-codeCompareDocs

Specifications

Context window262K tokens
Max output262K tokens
API typechat
AddedJun 13, 2026
Model IDparasail/kimi-k2.7-code
Data retentionNo
Used for trainingNo
Provider location🇺🇸 US
Privacy policyParasail 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 Parasail models overview.

Pricing

Input / 1M
$0.75
Output / 1M
$3.50
Cache write
N/A
Cache read / 1M
$0.16
Estimated cost
100K input + 10K output$0.11
1M input + 100K output$1.10
10M input + 1M output$11.00

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 parasail/kimi-k2.7-code.

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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="parasail/kimi-k2.7-code",
    messages=[
        {"role": "user", "content": "Explain quantum computing in one paragraph."},
    ],
)

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

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Frequently asked questions

How much does kimi-k2.7-code cost?
kimi-k2.7-code is priced at $0.75 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-k2.7-code?
kimi-k2.7-code 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-k2.7-code do?
kimi-k2.7-code supports vision input, tool calling, extended reasoning, prompt caching, structured outputs (JSON schema). You can call it through any OpenAI-compatible client by pointing base_url to Requesty.
How do I use kimi-k2.7-code 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 "parasail/kimi-k2.7-code". The Quickstart above shows Python, JavaScript and cURL snippets.
Can I run kimi-k2.7-code through Requesty?
Yes. kimi-k2.7-code runs through Requesty's OpenAI-compatible API, served from Parasail. You do not host the model yourself: point base_url at Requesty, set the model to "parasail/kimi-k2.7-code", and requests are routed to the upstream provider with automatic failover. The same key gives you 400+ other models too.

Access kimi-k2.7-code 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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