Requesty
Tencent

kimi-k2.7-code

Kimi's most intelligent coding model to date. It follows instructions more reliably across long contexts and achieves higher success rates on coding tasks. Supports text, image, and video inputs, as well as reasoning, chat, and agent workflows.

VisionReasoningTool callingCachingJSON schema
Try kimi-k2.7-codeCompareDocs

Specifications

Context window262K tokens
Max output262K tokens
API typechat
AddedJun 23, 2026
Model IDtencent/kimi-k2.7-code
Data retentionYes
Used for trainingNo
Provider location🇨🇳 China
Privacy policyTencent Cloud Privacy Policy→

Benchmarks

Released 2026-06-12
Coding Indexcoding
60.8%

Artificial Analysis Coding Index — a composite of coding evaluations including LiveCodeBench, SciCode and Terminal-Bench.

GPQA Diamondreasoning
89.6%

Graduate-level physics, chemistry & biology questions designed to resist Googling.

Intelligence Indexreasoning
41.9%

Artificial Analysis Intelligence Index — a composite of multiple evaluations measuring overall model capability.

Scores are sourced from official model cards, Artificial Analysis, and public leaderboards. Benchmarks measure specific skills and do not capture every aspect of model quality. Always test on your own workload.

Pricing

Input / 1M
$0.95
Output / 1M
$4.00
Cache write
N/A
Cache read / 1M
$0.19
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 tencent/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="tencent/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 $0.95 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-k2.7-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.
How does kimi-k2.7-code perform on benchmarks?
kimi-k2.7-code scores 90.1% on τ²-Bench, 89.6% on GPQA Diamond, 60.8% on Coding Index. See the full benchmark chart above for results across MMLU Pro, GPQA Diamond, SWE-Bench Verified, HumanEval, MATH, AIME, MMMU, and LiveBench.
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 "tencent/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 Tencent. You do not host the model yourself: point base_url at Requesty, set the model to "tencent/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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