Requesty
Fireworks AI

kimi-k2.5

Kimi K2.5 is an open-source, native multimodal agentic model built through continual pretraining on approximately 15 trillion mixed visual and text tokens atop Kimi-K2-Base. It seamlessly integrates vision and language understanding with advanced agentic capabilities, instant and thinking modes, as well as conversational and agentic paradigms.

👁Vision🧠Reasoning🔧Tool calling⚡Caching
Try kimi-k2.5CompareDocs

Specifications

Context window262K tokens
Max output262K tokens
API typechat
AddedMar 31, 2026
Model IDfireworks/kimi-k2.5
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
$0.60
Output / 1M
$3.00
Cache write / 1M
$3.00
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 fireworks/kimi-k2.5.

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
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-k2.5",
    messages=[
        {"role": "user", "content": "Explain quantum computing in one paragraph."},
    ],
)

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

Other Fireworks AI models

kimi-k2.6
262K ctx$0.95/1M
minimax-m2.5
197K ctx$0.30/1M
glm-5
203K ctx$1.00/1M
deepseek-v3.2
164K ctx$0.56/1M

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 "fireworks/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.

Get started freeAll Fireworks AI models