identity

open weights
Fireworks AI logo

kimi-k3Fireworks AI

in /1M$3.00input tokens
out /1M$15.00output tokens
context1M131K out
median ttft2.01smeasured
api
chat
hosting
US
model lab
Moonshot AI
weights
open
added
July 2026
model id
fireworks/kimi-k3

capabilities 5/8

visionreasoningtoolscachingweb searchjson schemacomputer useimage gen

5 providers serve kimi-k3. This page is one of them. Compare all endpoints

pricing

no markup
input
$3.00
output
$15.00
cache write
-
cache read
$0.30

worked cost

Estimated cost for three request volumes
volumecost
100K in + 10K out$0.45
1M in + 100K out$4.50
10M in + 1M out$45.00

Requesty charges what the upstream provider charges, with no markup and no per-request fee. Prompt caching and smart routing cut the effective cost further on repeated context. Gateway pricing

provider price, passed throughper 1M tokens

measured

through Sep 12
median ttft
2.01s
median tok/s
54.0
blended /1M
$0.90
cache hit
84.8%
answered
99.90%

Weekly aggregates from production traffic routed through Requesty to this endpoint. A metric with no qualifying sample is left out rather than filled in. Compare against the other providers

benchmarks

artificial analysis
Benchmark scores, each normalised to 100
evalScore as a share of 100/100
GPQA Diamond93.5
Coding Index76.2
SciCode59.5
Humanity's Last Exam46.9
Intelligence Index43.8
5 evalsmean64.0

Scores from Artificial Analysis and public leaderboards, normalised to 100. Bar colour is the band, not the rank: green 80 and up, blue 55 and up, amber 30 and up. Benchmarks measure narrow skills, so test on your own workload before committing. Released 2026-07-16.

policy

data terms
retention
none
trains on prompts
no
hosted in
US

Terms are the provider's, not Requesty's: routing a request here puts it under them. Fireworks Privacy Policy

Need every request to stay in one jurisdiction? EU hosting routes only through EU-hosted providers.

quickstart

openai compatible
fireworks/kimi-k3

this id pins the fireworks ai deployment, with no routing and no failover. the managed id on the canonical page routes across all 5 providers instead

main.py
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-k3",    messages=[        {"role": "user", "content": "Explain quantum computing in one paragraph."},    ],) print(response.choices[0].message.content)

Change the base url to https://router.requesty.ai/v1, use your Requesty key, set the model to the id above. Existing OpenAI SDK code needs no other edit, and the same key reaches every other model in the catalog. Browse all models

notes

reference

Kimi’s most capable flagship model to date, with 2.8 trillion parameters. It is built on Kimi Delta Attention (KDA), a hybrid linear attention mechanism, and Attention Residuals, with native visual understanding and a 1M-token context window. It is the world’s first open-source model in the 3-trillion-parameter class, designed for frontier intelligence scenarios including long-horizon coding, knowledge work, and reasoning.

questions 6

How much does kimi-k3 cost?
kimi-k3 is priced at $3.00 per million input tokens and $15.00 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-k3?
kimi-k3 has a context window of 1M tokens, with a maximum output of 131K tokens per response. That is roughly 1,333 words of input you can fit in a single prompt.
How does kimi-k3 perform on benchmarks?
kimi-k3 scores 93.5% on GPQA Diamond, 76.2% on Coding Index, 59.5% on SciCode. The benchmarks pane shows every published result, each normalised to 100.
What can kimi-k3 do?
kimi-k3 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-k3 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-k3". The quickstart pane shows Python, JavaScript and cURL snippets.
Can I run kimi-k3 through Requesty?
Yes. kimi-k3 runs through Requesty's OpenAI-compatible API, served from Fireworks AI. You do not host the model yourself: point base_url at Requesty, set the model to "fireworks/kimi-k3", and requests are routed to the upstream provider with automatic failover. The same key gives you 600+ other models too.

more from fireworks ai 8

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call kimi-k3 through one endpoint

One key for this endpoint and 600+ other models. No markup on provider prices, automatic failover when a provider degrades, and prompt caching built in. Methodology

kimi-k3fireworks aiin $3.00 /1Mout $15.00 /1Mctx 1Mttft 2.01shosted US5 providers serve this model