Featherless exposes Kimi K3 through model ID moonshotai/Kimi-K3. Use the setup steps, sourced pricing, capabilities, and official provider links below to validate this route before deployment.
Last refreshed 2026-09-24. Next refresh: weekly.
Quick Start
- 1
- 2Use the Featherless SDK or REST API to call
moonshotai/Kimi-K3— see the documentation for request format. - 3
Code Examples
pip install openaiFEATHERLESS_API_KEYmoonshotai/Kimi-K3Use exact Featherless catalog id in modelProvider.providerModelId (HF-style org/name). Not interchangeable with LLM Reference slugs.
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)Pricing on Featherless
| Type | Price (per 1M) |
|---|---|
| Input tokens | $3.00 |
| Output tokens | $15.00 |
Capabilities
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.
Model Specs
Provider