LLM Reference
Featherless

Kimi K3 on Featherless

Kimi · Moonshot AI

ServerlessOpen Weights

Last refreshed 2026-09-24. Next refresh: weekly.

Why use Kimi K3 on Featherless?

Featherless offers Kimi K3 with pay-as-you-go pricing at $3.00/1M input tokens. Featherless is a serverless inference provider for a large catalog of third-party open text-generation models (40,000+).

Compare Kimi K3 across 3 providers to find the best fit for your use case
Input / 1M
$3.00
Output / 1M
$15.00
Cache
Not sourced
Batch
Not sourced

Setup recipe

Python + curl
Install
pip install openai
Auth
export FEATHERLESS_API_KEY=...
Call
import os
from openai import OpenAI
client = OpenAI(
    base_url="https://api.featherless.ai/v1",
Model ID
moonshotai/Kimi-K3

Request example

import os
from openai import OpenAI

client = OpenAI(
    base_url="https://api.featherless.ai/v1",
    api_key=os.environ["FEATHERLESS_API_KEY"],
)
response = client.chat.completions.create(
    model="moonshotai/Kimi-K3",
    messages=[{"role": "user", "content": "Hello!"}],
)
print(response.choices[0].message.content)

Gotchas

  • Use provider model ID "moonshotai/Kimi-K3", not the LLMReference slug "kimi-k3".
  • Use exact Featherless catalog id in modelProvider.providerModelId (HF-style org/name). Not interchangeable with LLM Reference slugs.
  • The examples expect FEATHERLESS_API_KEY; rename it only if your application config maps the new variable.

Compare Kimi K3 Across Providers

ProviderInput (per 1M)Output (per 1M)
Moonshot AI Kimi$3.00$15.00
OpenRouter$2.00$11.20
Featherless$3.00$15.00

Pricing

TypePrice (per 1M)
Input tokens$3.00
Output tokens$15.00

Capabilities

VisionMultimodalReasoningJSON / Tool useStructured OutputsPrompt Caching

About Kimi K3

Kimi K3 is Moonshot AI's 2.8-trillion-parameter flagship multimodal model for long-horizon coding, knowledge work, deep reasoning, and agentic workflows. It uses Kimi Delta Attention, Attention Residuals, and a sparse MoE design (16 of 896 experts active), supports a 1,048,576-token context window, text/image/video input, always-on reasoning, ToolCalls, strict JSON Schema structured output, automatic context caching, and partial mode through Moonshot's OpenAI-compatible API.

Get Started

Model Specs

Released2026-07-14
Parameters2.8T total; 16 of 896 experts active
Context1.05m
ArchitectureMixture of Experts