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Fireworks AI

kimi-k2.6

Kimi K2.6 is an open-source, native multimodal agentic model that advances practical capabilities in long-horizon coding, coding-driven design, proactive autonomous execution, and swarm-based task orchestration. It features a 1028B Mixture-of-Experts architecture and supports vision, function calling, and agentic paradigms.

👁Vision🧠Reasoning🔧Tool calling⚡Caching
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Specifications

Context window262K tokens
Max output33K tokens
API typechat
AddedApr 24, 2026
Model IDfireworks/kimi-k2.6
Data retentionNo
Used for trainingNo
Provider location🇺🇸 US
Privacy policyFireworks 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 Fireworks AI models overview.

Pricing

Input / 1M
$0.95
Output / 1M
$4.00
Cache write
—
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 fireworks/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="fireworks/kimi-k2.6",
    messages=[
        {"role": "user", "content": "Explain quantum computing in one paragraph."},
    ],
)

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

Other Fireworks AI models

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197K ctx$0.30/1M
glm-5
203K ctx$1.00/1M
deepseek-v3.2
164K ctx$0.56/1M
kimi-k2.5
262K ctx$0.60/1M

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 33K 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 "fireworks/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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